AI Coder Youtube

AI Coder Youtube — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Inauthentic text

    Inauthentic text

    An inauthentic text is a computer-generated expository document meant to appear as genuine, but which is actually meaningless. Frequently they are created in order to be intermixed with genuine documents and thus manipulate the results of search engines, as with Spam blogs. They are also carried along in email in order to fool spam filters by giving the spam the superficial characteristics of legitimate text. Sometimes nonsensical documents are created with computer assistance for humorous effect, as with Dissociated press or Flarf poetry. They have also been used to challenge the veracity of a publication—MIT students submitted papers generated by a computer program called SCIgen to a conference, where they were initially accepted. This led the students to claim that the bar for submissions was too low. With the amount of computer generated text outpacing the ability of people to humans to curate it, there needs some means of distinguishing between the two. Yet automated approaches to determining absolutely whether a text is authentic or not face intrinsic challenges of semantics. Noam Chomsky coined the phrase "Colorless green ideas sleep furiously" giving an example of grammatically correct, but semantically incoherent sentence; some will point out that in certain contexts one could give this sentence (or any phrase) meaning. The first group to use the expression in this regard can be found below from Indiana University. Their work explains in detail an attempt to detect inauthentic texts and identify pernicious problems of inauthentic texts in cyberspace. The site has a means of submitting text that assesses, based on supervised learning, whether a corpus is inauthentic or not. Many users have submitted incorrect types of data and have correspondingly commented on the scores. This application is meant for a specific kind of data; therefore, submitting, say, an email, will not return a meaningful score.

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  • AMiner (database)

    AMiner (database)

    AMiner (formerly ArnetMiner) is a free online service used to index, search, and mine big scientific data. == Overview == AMiner (ArnetMiner) is designed to search and perform data mining operations against academic publications on the Internet, using social network analysis to identify connections between researchers, conferences, and publications. This allows it to provide services such as expert finding, geographic search, trend analysis, reviewer recommendation, association search, course search, academic performance evaluation, and topic modeling. AMiner was created as a research project in social influence analysis, social network ranking, and social network extraction. A number of peer-reviewed papers have been published arising from the development of the system. It has been in operation for more than three years, and has indexed 130,000,000 researchers and more than 265 million publications. The research was funded by the Chinese National High-tech R&D Program and the National Science Foundation of China. AMiner is commonly used in academia to identify relationships between and draw statistical correlations about research and researchers. It has attracted more than 10 million independent IP accesses from 220 countries and regions. The product has been used in Elsevier's SciVerse platform, and academic conferences such as SIGKDD, ICDM, PKDD, WSDM. == Operation == AMiner automatically extracts the researcher profile from the web. It collects and identifies the relevant pages, then uses a unified approach to extract data from the identified documents. It also extracts publications from online digital libraries using heuristic rules. It integrates the extracted researchers’ profiles and the extracted publications. It employs the researcher name as the identifier. A probabilistic framework has been proposed to deal with the name ambiguity problem in the integration. The integrated data is stored into a researcher network knowledge base (RNKB). The principal other product in the area are Google Scholar, Elsevier's Scirus, and the open source project CiteSeer. == History == It was initiated and created by professor Jie Tang from Tsinghua University, China. It was first launched in March 2006. The following provide a list of updates in the past years: March 2006, Version 0.1, Functions include researcher profiling, expert search, conference search, and publication search. The system was developed in Perl; August 2006, Version 1.0, The system was re-implemented in Java; July 2007, Version 2.0, New functions include researcher interest mining, association search, survey paper finding (unavailable now); April 2008, Version 3.0, New functions include query understanding, new GUI, and search log analysis; November 2008, Version 4.0, New functions include graph search, topic modeling, NSF/NSFC funding information extraction; April 2009, Version 5.0, New functions include Profile edition, open API service, Bole search, course search (unavailable now); December 2009, Version 6.0, New functions include academic performance evaluation, user feedback, conference analysis; May 2010, Version 7.0, New functions include name disambiguation, paper-reviewer recommendation, ArnetPage creation; March 2012, Version II, renamed as AMiner, rewrote all the codes and redesign the GUI. New functions include: geographic search, ArnetAPP platform. June 2014, Version II, renamed as AMiner, rewrote all the codes and redesign the GUI. New functions include: geographic search, ArnetAPP platform. December 2015, a completely new version got online. May 2017, professional version got online. April 2018, New functions include Trend Analysis, a deep learning based Name Disambiguation == Resources == AMiner published several datasets for academic research purpose, including Open Academic Graph, DBLP+citation (a data set augmenting citations into the DBLP data from Digital Bibliography & Library Project), Name Disambiguation, Social Tie Analysis. For more available datasets and source codes for research, please refer to.

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  • Content creation

    Content creation

    Content creation is the act of making and sharing media content, particularly in digital contexts. A content creator is the person or studio behind such content. According to Dictionary.com, content refers to "something that is to be expressed through some medium, as speech, writing or any of various arts" for self-expression, distribution, marketing and/or publication. Content creation encompasses various activities, including maintaining and updating web sites, blogging, article writing, photography, videography, online commentary, social media accounts, and editing and distribution of digital media. In a survey conducted by the Pew Research Center, the content thus created was defined as "the material people contribute to the online world". In addition to traditional forms of content creation, digital platforms face growing challenges related to privacy, copyright, misinformation, platform moderation policies, and the repercussions of violating community guidelines. == Content creators == Content creation is the process of producing and sharing various forms of content such as text, images, audio, and video, designed to engage and inform a specific audience. It plays a crucial role in digital marketing, branding, and online communication and brand awareness. Content can be created for a range of platforms, including social media, websites, blogs, and multimedia channels. Whether it's through written articles, compelling photography, or engaging videos, content creation helps businesses build a connection with their audience, increase visibility, and drive traffic. The process typically involves identifying the target audience, brainstorming ideas, creating the content, and distributing it across various channels. Successful content creation combines creativity with strategic planning, considering audience preferences, trends, and platform characteristics to achieve marketing and branding goals. === News organizations === News organizations, especially those with a large and global reach like The New York Times, NPR, and CNN, consistently create some of the most shared content on the Web, especially in relation to current events. In the words of a 2011 report from the Oxford School for the Study of Journalism and the Reuters Institute for the Study of Journalism, "Mainstream media is the lifeblood of topical social media conversations in the UK." While the rise of digital media has disrupted traditional news outlets, many have adapted and have begun to produce content that is designed to function on the web and be shared on social media. The social media site Twitter is a major distributor and aggregator of breaking news from various sources, and the function and value of Twitter in the distribution of news is a frequent topic of discussion and research in journalism. User-generated content, social media blogging and citizen journalism have changed the nature of news content in recent years. The company Narrative Science is now using artificial intelligence to produce news articles and interpret data. === Colleges, universities, and think tanks === Academic institutions, such as colleges and universities, create content in the form of books, journal articles, white papers, and some forms of digital scholarship, such as blogs that are group edited by academics, class wikis, or video lectures that support a massive open online course (MOOC). Through an open data initiative, institutions may make raw data supporting their experiments or conclusions available on the Web. Academic content may be gathered and made accessible to other academics or the public through publications, databases, libraries, and digital libraries. Academic content may be closed source or open access (OA). Closed-source content is only available to authorized users or subscribers. For example, an important journal or a scholarly database may be a closed source, available only to students and faculty through the institution's library. Open-access articles are open to the public, with the publication and distribution costs shouldered by the institution publishing the content. === Companies === Corporate content includes advertising and public relations content, as well as other types of content produced for profit, including white papers and sponsored research. Advertising can also include auto-generated content, with blocks of content generated by programs or bots for search engine optimization. Companies also create annual reports which are part of their company's workings and a detailed review of their financial year. This gives the stakeholders of the company insight into the company's current and future prospects and direction. === Artists and writers === Cultural works, like music, movies, literature, and art, are also major forms of content. Examples include traditionally published books and e-books as well as self-published books, digital art, fanfiction, and fan art. Independent artists, including authors and musicians, have found commercial success by making their work available on the Internet. === Government === Through digitization, sunshine laws, open records laws and data collection, governments may make statistical, legal or regulatory information available on the Internet. National libraries and state archives turn historical documents, public records, and unique relics into online databases and exhibits. This has raised significant privacy issues. In 2012, The Journal News, a New York state paper, sparked an outcry when it published an interactive map of the state's gun owner locations using legally obtained public records. Governments also create online or digital propaganda or misinformation to support domestic and international goals. This can include astroturfing, or using media to create a false impression of mainstream belief or opinion. Governments can also use open content, such as public records and open data, in service of public health, educational and scientific goals, such as crowdsourcing solutions to complex policy problems. In 2013, the National Aeronautics and Space Administration (NASA) joined the asteroid mining company Planetary Resources to crowdsource the hunt for near-Earth objects. Describing NASA's crowdsourcing work in an interview, technology transfer executive David Locke spoke of the "untapped cognitive surplus that exists in the world" which could be used to help develop NASA technology. In addition to making governments more participatory, open records and open data have the potential to make governments more transparent and less corrupt. === Users === The introduction of Web 2.0 made it possible for content consumers to be more involved in the generation and sharing of content. With the advent of digital media, the amount of user generated content, as well as the age and class range of users, has increased. 8% of Internet users are very active in content creation and consumption. Worldwide, about one in four Internet users are significant content creators, and users in emerging markets lead the world in engagement. Research has also found that young adults of a higher socioeconomic background tend to create more content than those from lower socioeconomic backgrounds. 69% of American and European internet users are "spectators", who consume—but do not create—online and digital media. The ratio of content creators to the amount of content they generate is sometimes referred to as the 1% rule, a rule of thumb that suggests that only 1% of a forum's users create nearly all of its content. Motivations for creating new content may include the desire to gain new knowledge, the possibility of publicity, or simple altruism. Users may also create new content in order to bring about social reforms. However, researchers caution that in order to be effective, context must be considered, a diverse array of people must be included, and all users must participate throughout the process. According to a 2011 study, minorities create content in order to connect with their communities online. African-American users have been found to create content as a means of self-expression that was not previously available. Media portrayals of minorities are sometimes inaccurate and stereotypical which affects the general perception of these minorities. African-Americans respond to their portrayals digitally through the use of social media such as Twitter and Tumblr. The creation of Black Twitter has allowed a community to share their problems and ideas. ==== Teens ==== Younger users now have greater access to content, content creating applications, and the ability to publish to different types of media, such as Facebook, Blogger, Instagram, DeviantArt, or Tumblr. As of 2005, around 21 million teens used the internet and 57%, or 12 million teens, consider themselves content creators. This proportion of media creation and sharing is higher than that of adults. With the advent of the Internet, teens have had more access to tools for sharing an

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  • Blend4Web

    Blend4Web

    Blend4Web is a free and open source framework for creating and displaying interactive 3D computer graphics in web browsers. == Overview == The Blend4Web framework leverages Blender to edit 3D scenes. Content rendering relies on WebGL, Web Audio, WebVR, and other web standards, without the use of plug-ins. It is dual-licensed. The framework is distributed under the free and open source GPLv3 and, a non-free license - with the source code being hosted on GitHub. A 3D scene can be prepared in Blender and then exported as a pair of JSON and binary files to load in a web application. It can also be exported as a single, self-contained HTML file, in which exported data, the web player GUI, and the engine itself are packed. The HTML option is considered to be the simplest way. The resulting file, which has a minimum size of 1 MB, can be embedded in a web page using a standard iframe HTML element. Blend4Web-powered web applications can be deployed on social networking websites such as Facebook. The Blend4Web toolchain consists of JavaScript libraries, the Blender add-on, and a set of tools for tweaking 3D scene parameters, debugging, and optimization. Developed by Moscow-based company Triumph in 2010, Blend4Web was publicly released on March 28, 2014. At the end of 2017, the project founders Yuri and Alex Kovelenov quit Triumph to start the development of a new WebGL framework Verge3D. In October 2019, an "Absolutely new Blend4Web" was announced, planned to make developing 3D apps easier and to add a new marketplace where people can offer their 3D models. == Features == The framework has a number of components typically found in game engines, including a positional audio system, physics engine (a fork of Bullet ported to JavaScript), animation system, and an abstraction layer for game logic programming. Up to 8 different types of animations can be assigned to a single object, including skeletal and per-vertex animation. The speed and the direction of animation (forward/backward play), as well as particle system parameters (size, initial velocity, and count), can be changed through the API. Among other supported features are: scene data dynamic loading and unloading, subsurface scattering simulation, and image-based lighting. Some out-of-box options exist for rendering extended outdoor environments, including foliage-wind interaction, water, atmosphere, and sunlight simulation. One example demonstrating these effects is "The Farm" tech demo, which also features multiple animated NPCs and the ability to walk, interact with objects and drive a vehicle in first-person mode. Being based on the cross-browser WebGL API, Blend4Web runs in the majority of web browsers, including mobile ones. There are some caveats for browsers with experimental WebGL support, such as Internet Explorer. There are also applications developed to run on Tizen-powered devices such as the Samsung Gear S2 smartwatch. Other features include: draw call batching, hidden surface determination, threaded physics simulation and ocean simulation. In version 14.09, Blend4Web introduced the possibility of adding interactivity to 3D scenes using a visual programming tool. The tool is reminiscent of the BGE's logic editor as it uses logic blocks that are placed inside Blender. It plays back animation tracks authored by an artist when the user interacts with predefined 3D objects. Since version 15.03, Blend4Web has supported attaching HTML elements (such as information windows) to 3D objects ("annotations") and copying objects in run time ("instancing"). The following post-processing effects are supported: glow, bloom, depth of field, crepuscular rays, motion blur, and screen space ambient occlusion. == Virtual reality and augmented reality == Virtual reality devices have been supported since the end of 2015. Specifically, Oculus Rift head-mounted display works over experimental WebVR API. The software also now includes preliminary support for gamepads, based on the Gamepad API. In 2017, the option to author augmented reality content was added. The system is based on the open-source tracking library ARToolKit and uses the WebRTC protocols. Starting from version 17.08, finger tracking is supported through the Leap Motion device. == Blender integration == The Blender add-on is written in Python and C and can be compiled for the Linux x86/x64, OS X x64, and MS Windows x86/x64 platforms. A Blend4Web-specific profile can be activated in the add-on settings. When switching to this profile, the Blender interface changes so that it only reveals settings relevant to Blend4Web. Blend4Web supports a set of Blender-specific features such as the node material editor (a tool for visual shader programming) and the particle system. There is basic support for Blender's non-linear animation (NLA) editor for creating simple scenarios. Blend4Web is based on Blender's real-time GLSL rendering engine, which users are recommended to use in order to enable WYSIWYG editing. == Notable uses == NASA developed an interactive web application called Experience Curiosity to celebrate the 3rd anniversary of the Curiosity rover landing on Mars. This Blend4Web-based app makes it possible to operate the rover, control its cameras and the robotic arm, and reproduce some of the prominent events of the Mars Science Laboratory mission. The application got presented at the beginning of the WebGL section at SIGGRAPH 2015. Experience Curiosity was ported to Verge3D for Blender in 2018 with several performance improvements and bug fixes. A General Motors authorized dealer in the United Arab Emirates has placed a functional Chevrolet Camaro 3D configurator on its website. Greenpeace created interactive 3D infographics to back Greenpeace's Detox campaign in Russia. Tallink featured an interactive 3D presentation of its MS Megastar vessel to allow visitors to browse details of the ship.

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  • JSGF

    JSGF

    JSGF stands for Java Speech Grammar Format or the JSpeech Grammar Format (in a W3C Note). Developed by Sun Microsystems, it is a textual representation of grammars for use in speech recognition for technologies like XHTML+Voice. JSGF adopts the style and conventions of the Java programming language in addition to use of traditional grammar notations. The Speech Recognition Grammar Specification was derived from this specification. == Example == The following JSGF grammar will recognize the words coffee, tea, and milk.

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  • Contact center telephony

    Contact center telephony

    In marketing, contact center telephony is the communication and collaboration system used by businesses to either manage high volumes of inbound queries or outbound telephone calls keeping their workforce or agents productive and in control to serve or acquire customers. This business communication system is an extension of computer telephony integration (CTI). == Overview == The interactions between callers and customer service representatives are supported by the collective system of computers, telephones and the Internet. The shift from CTI to contact center telephony is marked by the sheer change in the customer’s behavior when it comes to communication. Means customers are no longer confined only to voice-based communication i.e. phone to connect with their customer service departments. In addition, they are making use of email, SMS, chat, social media, and other virtual contact channels. This is also the reason for the shift in nomenclature from "call centers" to "contact centers", "contact" being a wider term than "call". Respecting the trend, contact center owners need to adopt unified communication or multi-channel approach to let customers get in touch with them via their preferred communication mediums, either voice or non-voice (data). Cloud-based phone system is a further advancement in the direction as it allows operators to access all the features and benefits of call center telephony over the Web against an affordable & flexible pay-as-you-go subscription model. Thus, in-house infrastructure deployment to manage public switched telephone networks, storage, communication applications, and collaboration servers is no more an obligation. Neither is the need to invest resources for their upgrade, repair, maintenance and security as cloud vendor would be responsible for the same. == India == India, a popular call center business process outsourcing destination, often uses a cloud-based phone system in order to cut operational expenses and downtime, and increase connectivity. == Promotion == Businesses can rely on contact center telephony services to respond to their customers’ queries over phone, email, chat, fax, etc. Integrating it with their customer relationship management tools, entire contact details of customers and their interaction sessions with different customer service representatives can be found at one place. The combination can manage not just sales and marketing but also deliver excellent post-sales customer service or technical support to allow customers derive the most from their products or services. Hence, it’s becoming instrumental in increasing customer satisfaction and loyalty and most of the call center services in India are taking refuge from it. The entire contact center telephony service can be availed by professionals over a browser. Hence, businesses can leverage the concept of BYOD (bring your own device) and mobility and serve their customers well using mobile applications. According to market analysts, BYOD increases satisfaction among workforce, and hence their individual and collective productivity as well. BYOD programme significantly reduces the TCO (total cost of ownership) as professionals prefer to work with their own devices rather than using company-provisioned devices. Next, they tend to be more caring towards such devices and can even shell out money to update and upgrade those when required. Integration of IM, along with audio and video conferencing services helps call center or contact center representatives to get real time assistance from their peers or seniors to resolve any complex issues. They can internally exchange information and knowledge articles as and when required. Real-time call monitoring/barging system can be used by quality assessment team to provide important guidelines to agents to maintain the standard of the service as per industry norms. Integrated recording feature is helpful for internal training and quality purposes to improve productivity and customer satisfaction in equal measures. It also helps in getting business insights and improving products or services to gain deeper penetration into the market.

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  • Online exhibition

    Online exhibition

    An online exhibition, also referred to as a virtual exhibition, online gallery, cyber-exhibition, is an exhibition whose venue is cyberspace. Museums and other organizations create online exhibitions for many reasons. For example, an online exhibition may: expand on material presented at, or generate interest in, or create a durable online record of, a physical exhibition; save production costs (insurance, shipping, installation); solve conservation/preservation problems (e.g., handling of fragile or rare objects); reach lots more people: "Access to information is no longer restricted to those who can afford travel and museum visits, but is available to anyone who has access to a computer with an Internet connection. Unlike physical exhibitions, online exhibitions are not restricted by time; they are not forced to open and close but may be available 24 hours a day. In the nonprofit world, many museums, libraries, archives, universities, and other cultural organizations create online exhibitions. A database of such exhibitions is Library and Archival Exhibitions on the Web. Online exhibition organizers may use techniques such as marquee text, display advertisements, and in-event emails to engage patrons. Various guides have been published to help organizations create effective online exhibitions. The earliest museum with a physical existence to create a programme of substantial online exhibitions with high resolution images of artefacts was the Museum of the History of Science in Oxford, the first of which, The Measurers: a Flemish Image of Mathematics in the Sixteenth Century and an exhibition of early photographs, were published on 21 August 1995. == Examples of online exhibitions == International Museum of Women is an online-only museum that does not have a physical building and instead offers online exhibitions about women's issues globally as well as an online community. Online exhibitions include "Imagining Ourselves" (launched 2006) about women's identity, "Women, Power and Politics" (2008), and "Economica: Women and the Global Economy" (2009). Tucson LGBTQ Museum is an online-only museum that does not have a physical building and instead offers online exhibitions about LGBTQ history. The online photographic, audio, video, text, and other historical exhibitions include exhibits from the 1700s to the present day. The effort began in the summer of 1967 and spanned almost 50 years. International New Media Gallery (INMG) is an online museum specialising in moving image and screen-based art. The INMG is dedicated to exploring current debates and topics in art history: touching on areas such as migration, war, environmental activism and the internet itself. The gallery publishes extensive academic catalogues alongside its exhibitions. It also hosts spaces for discussion and debate, both online and offline. Virtual Museum of Modern Nigerian Art – the VMMNA is the first of its kind in Africa. Hosted by the Pan-African University, Lagos, Nigeria this virtual museum offers a good view of the development on Nigerian Art in the past fifty years.

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  • Svelte

    Svelte

    Svelte is a free and open-source component-based front-end software framework and language created by Rich Harris and maintained by the Svelte core team. Svelte is not a monolithic JavaScript library imported by applications: instead, Svelte compiles HTML templates to specialized code that manipulates the DOM directly, which may reduce the size of transferred files and give better client performance. Application code is also processed by the compiler, inserting calls to automatically recompute data and re-render UI elements when the data they depend on is modified. This also avoids the overhead associated with runtime intermediate representations, such as virtual DOM, unlike traditional frameworks (such as React and Vue) which carry out the bulk of their work at runtime, i.e. in the browser. The compiler itself is written in JavaScript. Its source code is licensed under MIT License and hosted on GitHub. Among comparable frontend libraries, Svelte has one of the smallest bundle footprints at merely 2KB. == History == The predecessor of Svelte is Ractive.js, which Rich Harris created in 2013. Version 1 of Svelte was written in JavaScript and was released on 29 November 2016. The name Svelte was chosen by Rich Harris and his coworkers at The Guardian. Version 2 of Svelte was released on 19 April 2018. It set out to correct what the maintainers viewed as mistakes in the earlier version such as replacing double curly braces with single curly braces. Version 3 of Svelte was written in TypeScript and was released on 21 April 2019. It rethought reactivity by using the compiler to instrument assignments behind the scenes. The SvelteKit web framework was announced in October 2020 and entered beta in March 2021. SvelteKit 1.0 was released in December 2022 after two years in development. Version 4 of Svelte was released on 22 June 2023. It was a maintenance release, smaller and faster than version 3. A part of this release was an internal rewrite from TypeScript back to JavaScript, with JSDoc type annotations. This was met with confusion from the developer community, which was addressed by the creator of Svelte, Rich Harris. Version 5 of Svelte was released on October 19, 2024 at Svelte Summit Fall 2024 with Rich Harris cutting the release live while joined by other Svelte maintainers. Svelte 5 was a ground-up rewrite of Svelte, changing core concepts such as reactivity and reusability. Its primary feature, runes, reworked how reactive state is declared and used. Runes are function-like macros that are used to declare a reactive state, or code that uses reactive states. These runes are used by the compiler to indicate values that may change and are depended on by other states or the DOM. Svelte 5 also introduces Snippets, which are reusable "snippets" of code that are defined once and can be reused anywhere else in the component. Svelte 5 was initially met with controversy due to its many changes, and thus deprecations caused primarily by runes. However, most of this has subsided since the initial announcement of runes, and the further refining of Svelte 5. Also at Svelte Summit Fall 2024, Ben McCann announced the Svelte CLI under the sv package name on npm. In early 2025, the Svelte team announced Asynchronous Svelte, an experimental feature set centered around asynchronous reactivity in Svelte using await expressions. As of August 2025, the feature is available via an experimental compiler option. This coincided with the experimental release of remote functions, an RPC feature in SvelteKit, Svelte's metaframework. Key early contributors to Svelte became involved with Conduitry joining with the release of Svelte 1, Tan Li Hau joining in 2019, and Ben McCann joining in 2020. Rich Harris and Simon Holthausen joined Vercel to work on Svelte fulltime in 2022. Dominic Gannaway joined Vercel from the React core team to work on Svelte fulltime in 2023. == Syntax == Svelte applications and components are defined in .svelte files, which are HTML files extended with templating syntax that is based on JavaScript and is similar to JSX. Svelte's core features are accessed through runes, which syntactically look like functions, but are used as macros by the compiler. These runes include: The $state rune, used for declaring a reactive state value The $derived rune, used for declaring reactive state derived from one or more states The $effect rune, used for declaring code that reruns whenever its dependencies change Starting with Svelte 5, the framework introduced a significant reactivity overhaul that replaces the previous `$:` reactive declarations with new runes such as $state, $derived, and $effect. The $effect rune is now used for post-render operations without modifying state, while $derived is used for computations that depend on other reactive values. This change aims to simplify the mental model of reactivity and make component logic more explicit. Additionally, the { JavaScript code } syntax can be used for templating in HTML elements and components, similar to template literals in JavaScript. This syntax can also be used in element attributes for uses such as two-way data binding, event listeners, and CSS styling. A Todo List example made in Svelte is below: == Associated projects == The Svelte maintainers created SvelteKit as the official way to build projects with Svelte. It is a Next.js/Nuxt-style full-stack framework that dramatically reduces the amount of code that gets sent to the browser. The maintainers had previously created Sapper, which was the predecessor of SvelteKit. The Svelte maintainers also maintain a number of integrations for popular software projects under the Svelte organization including integrations for Vite, Rollup, Webpack, TypeScript, VS Code, Chrome Developer Tools, ESLint, and Prettier. A number of external projects such as Storybook have also created integrations with Svelte and SvelteKit. == Influence == Vue.js modeled its API and single-file components after Ractive.js, the predecessor of Svelte. == Adoption == Svelte is widely praised by developers. Taking the top ranking in multiple large scale developer surveys, it was chosen as the Stack Overflow 2021 most loved web framework and 2020 State of JS frontend framework with the most satisfied developers. Recent surveys continue to show Svelte's strong developer satisfaction, with the 2024 State of JS survey maintaining its position among the most praised frontend frameworks. The 2024 Stack Overflow Developer Survey reported that 73% of developers who used Svelte want to continue working with it, and noted that Stack Overflow's own team used Svelte for building their 2024 Developer Survey results site. Svelte has been adopted by a number of high-profile web companies including The New York Times, Google, Apple, Spotify, Radio France, Square, Yahoo, ByteDance, Rakuten, Bloomberg, Reuters, Ikea, Facebook, Logitech, and Brave. A community group of primarily non-maintainers, known as the Svelte Society, run the Svelte Summit conference, write a Svelte newsletter, host a Svelte podcast, and host a directory of Svelte tooling, components, and templates.

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  • Rademacher complexity

    Rademacher complexity

    In computational learning theory (machine learning and theory of computation), Rademacher complexity, named after Hans Rademacher, measures richness of a class of sets with respect to a probability distribution. The concept can also be extended to real valued functions. == Definitions == === Rademacher complexity of a set === Given a set A ⊆ R m {\displaystyle A\subseteq \mathbb {R} ^{m}} , the Rademacher complexity of A is defined as follows: Rad ⁡ ( A ) := 1 m E σ [ sup a ∈ A ∑ i = 1 m σ i a i ] {\displaystyle \operatorname {Rad} (A):={\frac {1}{m}}\mathbb {E} _{\sigma }\left[\sup _{a\in A}\sum _{i=1}^{m}\sigma _{i}a_{i}\right]} where σ 1 , σ 2 , … , σ m {\displaystyle \sigma _{1},\sigma _{2},\dots ,\sigma _{m}} are independent random variables drawn from the Rademacher distribution i.e. Pr ( σ i = + 1 ) = Pr ( σ i = − 1 ) = 1 / 2 {\displaystyle \Pr(\sigma _{i}=+1)=\Pr(\sigma _{i}=-1)=1/2} for i ∈ { 1 , 2 , … , m } {\displaystyle i\in \{1,2,\dots ,m\}} , and a = ( a 1 , … , a m ) ∈ A {\displaystyle a=(a_{1},\ldots ,a_{m})\in A} . Some authors take the absolute value of the sum before taking the supremum, but if A {\displaystyle A} is symmetric this makes no difference. === Rademacher complexity of a function class === Let S = { z 1 , z 2 , … , z m } ⊆ Z {\displaystyle S=\{z_{1},z_{2},\dots ,z_{m}\}\subseteq Z} be a sample of points and consider a function class F {\displaystyle {\mathcal {F}}} of real-valued functions over Z {\displaystyle Z} . Then, the empirical Rademacher complexity of F {\displaystyle {\mathcal {F}}} given S {\displaystyle S} is defined as: Rad S ⁡ ( F ) = 1 m E σ [ sup f ∈ F | ∑ i = 1 m σ i f ( z i ) | ] {\displaystyle \operatorname {Rad} _{S}({\mathcal {F}})={\frac {1}{m}}\mathbb {E} _{\sigma }\left[\sup _{f\in {\mathcal {F}}}\left|\sum _{i=1}^{m}\sigma _{i}f(z_{i})\right|\right]} This can also be written using the previous definition: Rad S ⁡ ( F ) = Rad ⁡ ( F ∘ S ) {\displaystyle \operatorname {Rad} _{S}({\mathcal {F}})=\operatorname {Rad} ({\mathcal {F}}\circ S)} where F ∘ S {\displaystyle {\mathcal {F}}\circ S} denotes function composition, i.e.: F ∘ S := { ( f ( z 1 ) , … , f ( z m ) ) ∣ f ∈ F } {\displaystyle {\mathcal {F}}\circ S:=\{(f(z_{1}),\ldots ,f(z_{m}))\mid f\in {\mathcal {F}}\}} The worst case empirical Rademacher complexity is Rad ¯ m ( F ) = sup S = { z 1 , … , z m } Rad S ⁡ ( F ) {\displaystyle {\overline {\operatorname {Rad} }}_{m}({\mathcal {F}})=\sup _{S=\{z_{1},\dots ,z_{m}\}}\operatorname {Rad} _{S}({\mathcal {F}})} Let P {\displaystyle P} be a probability distribution over Z {\displaystyle Z} . The Rademacher complexity of the function class F {\displaystyle {\mathcal {F}}} with respect to P {\displaystyle P} for sample size m {\displaystyle m} is: Rad P , m ⁡ ( F ) := E S ∼ P m [ Rad S ⁡ ( F ) ] {\displaystyle \operatorname {Rad} _{P,m}({\mathcal {F}}):=\mathbb {E} _{S\sim P^{m}}\left[\operatorname {Rad} _{S}({\mathcal {F}})\right]} where the above expectation is taken over an identically independently distributed (i.i.d.) sample S = ( z 1 , z 2 , … , z m ) {\displaystyle S=(z_{1},z_{2},\dots ,z_{m})} generated according to P {\displaystyle P} . == Intuition == The Rademacher complexity is typically applied on a function class of models that are used for classification, with the goal of measuring their ability to classify points drawn from a probability space under arbitrary labellings. When the function class is rich enough, it contains functions that can appropriately adapt for each arrangement of labels, simulated by the random draw of σ i {\displaystyle \sigma _{i}} under the expectation, so that this quantity in the sum is maximized. The Rademacher complexity of a set A {\displaystyle A} can be rewritten as Rad ⁡ ( A ) := 1 m E σ [ sup a ∈ A ∑ i = 1 m σ i a i ] = 1 m 2 m ∑ σ ∈ { − 1 / m , + 1 / m } m [ sup a ∈ A ⟨ σ , a ⟩ ] . {\displaystyle \operatorname {Rad} (A):={\frac {1}{m}}\mathbb {E} _{\sigma }\left[\sup _{a\in A}\sum _{i=1}^{m}\sigma _{i}a_{i}\right]={\frac {1}{{\sqrt {m}}2^{m}}}\sum _{\sigma \in \{-1/{\sqrt {m}},+1/{\sqrt {m}}\}^{m}}\left[\sup _{a\in A}\langle \sigma ,a\rangle \right].} Each term in the summation is the farthest distance of the set A {\displaystyle A} from the origin, along a unit-length direction σ {\displaystyle \sigma } . The directions are along the vertices of a hypercube. Thus, we can also write it as Rad ⁡ ( A ) = 1 2 m 1 2 m − 1 ∑ σ ∈ { − 1 / m , + 1 / m } m / { − 1 , + 1 } [ sup a ∈ A ⟨ σ , a ⟩ − inf a ∈ A ⟨ σ , a ⟩ ] {\displaystyle \operatorname {Rad} (A)={\frac {1}{2{\sqrt {m}}}}{\frac {1}{2^{m-1}}}\sum _{\sigma \in \{-1/{\sqrt {m}},+1/{\sqrt {m}}\}^{m}/\{-1,+1\}}\left[\sup _{a\in A}\langle \sigma ,a\rangle -\inf _{a\in A}\langle \sigma ,a\rangle \right]} Here, the set { − 1 / m , + 1 / m } m / { − 1 , + 1 } {\displaystyle \{-1/{\sqrt {m}},+1/{\sqrt {m}}\}^{m}/\{-1,+1\}} denotes half of the vertices of a hypercube, selected so that each diagonal has exactly one vertex selected. In words, this states that 2 m Rad ⁡ ( A ) {\displaystyle 2{\sqrt {m}}\operatorname {Rad} (A)} is precisely the average width of the set A {\displaystyle A} along all diagonal directions of a hypercube. == Examples == A singleton set has 0 width in any direction, so it has Rademacher complexity 0. The set A = { ( 1 , 1 ) , ( 1 , 2 ) } ⊆ R 2 {\displaystyle A=\{(1,1),(1,2)\}\subseteq \mathbb {R} ^{2}} has average width 1 / 2 {\displaystyle 1/{\sqrt {2}}} along the two diagonal directions of the square, so it has Rademacher complexity 1 / 4 {\displaystyle 1/4} . The unit cube [ 0 , 1 ] m {\displaystyle [0,1]^{m}} has constant width m {\displaystyle {\sqrt {m}}} along the diagonal directions, so it has Rademacher complexity 1 / 2 {\displaystyle 1/2} . Similarly, the unit cross-polytope { x ∈ R m : ‖ x ‖ 1 ≤ 1 } {\displaystyle \{x\in \mathbb {R} ^{m}:\|x\|_{1}\leq 1\}} has constant width 2 / m {\displaystyle 2/{\sqrt {m}}} along the diagonal directions, so it has Rademacher complexity 1 / m {\displaystyle 1/m} . == Using the Rademacher complexity == The Rademacher complexity can be used to derive data-dependent upper-bounds on the learnability of function classes. Intuitively, a function-class with smaller Rademacher complexity is easier to learn. === Bounding the representativeness === In machine learning, it is desired to have a training set that represents the true distribution of some sample data S {\displaystyle S} . This can be quantified using the notion of representativeness. Denote by P {\displaystyle P} the probability distribution from which the samples are drawn. Denote by H {\displaystyle H} the set of hypotheses (potential classifiers) and denote by F {\displaystyle {\mathcal {F}}} the corresponding set of error functions, i.e., for every hypothesis h ∈ H {\displaystyle h\in H} , there is a function f h ∈ F {\displaystyle f_{h}\in F} , that maps each training sample (features,label) to the error of the classifier h {\displaystyle h} (note in this case hypothesis and classifier are used interchangeably). For example, in the case that h {\displaystyle h} represents a binary classifier, the error function is a 0–1 loss function, i.e. the error function f h {\displaystyle f_{h}} returns 0 if h {\displaystyle h} correctly classifies a sample and 1 else. We omit the index and write f {\displaystyle f} instead of f h {\displaystyle f_{h}} when the underlying hypothesis is irrelevant. Define: L P ( f ) := E z ∼ P [ f ( z ) ] {\displaystyle L_{P}(f):=\mathbb {E} _{z\sim P}[f(z)]} – the expected error of some error function f ∈ F {\displaystyle f\in {\mathcal {F}}} on the real distribution P {\displaystyle P} ; L S ( f ) := 1 m ∑ i = 1 m f ( z i ) {\displaystyle L_{S}(f):={1 \over m}\sum _{i=1}^{m}f(z_{i})} – the estimated error of some error function f ∈ F {\displaystyle f\in {\mathcal {F}}} on the sample S {\displaystyle S} . The representativeness of the sample S {\displaystyle S} , with respect to P {\displaystyle P} and F {\displaystyle {\mathcal {F}}} , is defined as: Rep P ⁡ ( F , S ) := sup f ∈ F ( L P ( f ) − L S ( f ) ) {\displaystyle \operatorname {Rep} _{P}({\mathcal {F}},S):=\sup _{f\in F}(L_{P}(f)-L_{S}(f))} Smaller representativeness is better, since it provides a way to avoid overfitting: it means that the true error of a classifier is not much higher than its estimated error, and so selecting a classifier that has low estimated error will ensure that the true error is also low. Note however that the concept of representativeness is relative and hence can not be compared across distinct samples. The expected representativeness of a sample can be bounded above by the Rademacher complexity of the function class: If F {\displaystyle {\mathcal {F}}} is a set of functions with range within [ 0 , 1 ] {\displaystyle [0,1]} , then Rad P , m ⁡ ( F ) − ln ⁡ 2 2 m ≤ E S ∼ P m [ Rep P ⁡ ( F , S ) ] ≤ 2 Rad P , m ⁡ ( F ) {\displaystyle \operatorname {Rad} _{P,m}({\mathcal {F}})-{\sqrt {\frac {\ln 2}{2m}}}\leq \mathbb {E} _{S\sim P^{m}}[\operatorname {Rep} _{P}({\

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  • Asynchronous module definition

    Asynchronous module definition

    Asynchronous module definition (AMD) is a specification for the programming language JavaScript. It defines an application programming interface (API) that defines code modules and their dependencies, and loads them asynchronously if desired. Implementations of AMD provide the following benefits: Website performance improvements. AMD implementations load smaller JavaScript files, and then only when they are needed. Fewer page errors. AMD implementations allow developers to define dependencies that must load before a module is executed, so the module does not try to use outside code that is not available yet.... In addition to loading multiple JavaScript files at runtime, AMD implementations allow developers to encapsulate code in smaller, more logically-organized files, in a way similar to other programming languages such as Java. For production and deployment, developers can concatenate and minify JavaScript modules based on an AMD API into one file, the same as traditional JavaScript. AMD provides some CommonJS interoperability. It allows for using a similar exports and require() interface in the code, although its own define() interface is more basal and preferred. The AMD specification is implemented by Dojo Toolkit, RequireJS, and other libraries.

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  • Common-mode signal

    Common-mode signal

    In electrical engineering, a common-mode signal is the identical component of voltage present at both input terminals of an electrical device. In telecommunication, the common-mode signal on a transmission line is also known as longitudinal voltage. Common-mode interference (CMI) is a type of common-mode signal. Common-mode interference is interference that appears on both signal leads, or coherent interference that affects two or more elements of a network. In most electrical circuits, desired signals are transferred by a differential voltage between two conductors. If the voltages on these conductors are U1 and U2, the common-mode signal is the average of the voltages: U cm = U 1 + U 2 2 {\displaystyle U_{\text{cm}}={\frac {U_{1}+U_{2}}{2}}} When referenced to the local common or ground, a common-mode signal appears on both lines of a two-wire cable, in phase and with equal amplitudes. Technically, a common-mode voltage is one-half the vector sum of the voltages from each conductor of a balanced circuit to local ground or common. Such signals can arise from one or more of the following sources: Radiated signals coupled equally to both lines, An offset from signal common created in the driver circuit, or A ground differential between the transmitting and receiving locations. Noise induced into a cable, or transmitted from a cable, usually occurs in the common mode, as the same signal tends to be picked up by both conductors in a two-wire cable. Likewise, RF noise transmitted from a cable tends to emanate from both conductors. Elimination of common-mode signals on cables entering or leaving electronic equipment is important to ensure electromagnetic compatibility. Unless the intention is to transmit or receive radio signals, an electronic designer generally designs electronic circuits to minimise or eliminate common-mode effects. == Methods of eliminating common-mode signals == Differential amplifiers or receivers that respond only to voltage differences, e.g. those between the wires that constitute a pair. This method is particularly suited for instrumentation where signals are transmitted through DC bias. For sensors with very high output impedance that require very high common-mode rejection ratio, a differential amplifier is combined with input buffers to form an instrumentation amplifier. An inductor where a pair of signaling wires follow the same path through the inductor, e.g. in a bifilar winding configuration such as used in Ethernet magnetics. Useful for AC and DC signals, but will filter only higher frequency common-mode signals. A transformer, which is useful for AC signals only, and will filter any form of common-mode noise, but may be used in combination with a bifilar wound coil to eliminate capacitive coupling of higher frequency common-mode signals across the transformer. Used in twisted pair Ethernet. Common-mode filtering may also be used to prevent egress of noise for electromagnetic compatibility purposes: High frequency common-mode signals (e.g., RF noise from a computing circuit) may be blocked using a ferrite bead clamped to the outside of a cable. These are often observable on laptop computer power supplies near the jack socket, and good quality mouse or printer USB cables and HDMI cables. Switch mode power supplies include common and differential mode filtering inductors to block the switching signal noise returning into mains wiring. Common-mode rejection ratio is a measure of how well a circuit eliminates common-mode interference.

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  • Harmonic

    Harmonic

    In physics, acoustics, and telecommunications, a harmonic is a sinusoidal wave with a frequency that is a positive integer multiple of the fundamental frequency of a periodic signal. The fundamental frequency is also called the 1st harmonic; the other harmonics are known as higher harmonics. As all harmonics are periodic at the fundamental frequency, the sum of harmonics is also periodic at that frequency. The set of harmonics forms a harmonic series. The term is employed in various disciplines, including music, physics, acoustics, electronic power transmission, radio technology, and other fields. For example, if the fundamental frequency is 50 Hz, a common AC power supply frequency, the frequencies of the first three higher harmonics are 100 Hz (2nd harmonic), 150 Hz (3rd harmonic), 200 Hz (4th harmonic) and any addition of waves with these frequencies is periodic at 50 Hz. An n {\displaystyle \ n} th characteristic mode, for n > 1 , {\displaystyle \ n>1\ ,} will have nodes that are not vibrating. For example, the 3rd characteristic mode will have nodes at 1 3 L {\displaystyle \ {\tfrac {1}{3}}\ L\ } and 2 3 L , {\displaystyle \ {\tfrac {2}{3}}\ L\ ,} where L {\displaystyle \ L\ } is the length of the string. In fact, each n {\displaystyle \ n} th characteristic mode, for n {\displaystyle \ n\ } not a multiple of 3, will not have nodes at these points. These other characteristic modes will be vibrating at the positions 1 3 L {\displaystyle \ {\tfrac {1}{3}}\ L\ } and 2 3 L . {\displaystyle \ {\tfrac {2}{3}}\ L~.} If the player gently touches one of these positions, then these other characteristic modes will be suppressed. The tonal harmonics from these other characteristic modes will then also be suppressed. Consequently, the tonal harmonics from the n {\displaystyle \ n} th characteristic characteristic modes, where n {\displaystyle \ n\ } is a multiple of 3, will be made relatively more prominent. In music, harmonics are used on string instruments and wind instruments as a way of producing sound on the instrument, particularly to play higher notes and, with strings, obtain notes that have a unique sound quality or "tone colour". On strings, bowed harmonics have a "glassy", pure tone. On stringed instruments, harmonics are played by touching (but not fully pressing down the string) at an exact point on the string while sounding the string (plucking, bowing, etc.); this allows the harmonic to sound, a pitch which is always higher than the fundamental frequency of the string. == Terminology == Harmonics may be called "overtones", "partials", or "upper partials", and in some music contexts, the terms "harmonic", "overtone" and "partial" are used fairly interchangeably. But more precisely, the term "harmonic" includes all pitches in a harmonic series (including the fundamental frequency) while the term "overtone" only includes pitches above the fundamental. == Characteristics == A whizzing, whistling tonal character, distinguishes all the harmonics both natural and artificial from the firmly stopped intervals; therefore their application in connection with the latter must always be carefully considered. Most acoustic instruments emit complex tones containing many individual partials (component simple tones or sinusoidal waves), but the untrained human ear typically does not perceive those partials as separate phenomena. Rather, a musical note is perceived as one sound, the quality or timbre of that sound being a result of the relative strengths of the individual partials. Many acoustic oscillators, such as the human voice or a bowed violin string, produce complex tones that are more or less periodic, and thus are composed of partials that are nearly matched to the integer multiples of fundamental frequency and therefore resemble the ideal harmonics and are called "harmonic partials" or simply "harmonics" for convenience (although it's not strictly accurate to call a partial a harmonic, the first being actual and the second being theoretical). Oscillators that produce harmonic partials behave somewhat like one-dimensional resonators, and are often long and thin, such as a guitar string or a column of air open at both ends (as with the metallic modern orchestral transverse flute). Wind instruments whose air column is open at only one end, such as trumpets and clarinets, also produce partials resembling harmonics. However they only produce partials matching the odd harmonics—at least in theory. In practical use, no real acoustic instrument behaves as perfectly as the simplified physical models predict; for example, instruments made of non-linearly elastic wood, instead of metal, or strung with gut instead of brass or steel strings, tend to have not-quite-integer partials. Partials whose frequencies are not integer multiples of the fundamental are referred to as inharmonic partials. Some acoustic instruments emit a mix of harmonic and inharmonic partials but still produce an effect on the ear of having a definite fundamental pitch, such as pianos, strings plucked pizzicato, vibraphones, marimbas, and certain pure-sounding bells or chimes. Antique singing bowls are known for producing multiple harmonic partials or multiphonics. Other oscillators, such as cymbals, drum heads, and most percussion instruments, naturally produce an abundance of inharmonic partials and do not imply any particular pitch, and therefore cannot be used melodically or harmonically in the same way other instruments can. Building on of Sethares (2004), dynamic tonality introduces the notion of pseudo-harmonic partials, in which the frequency of each partial is aligned to match the pitch of a corresponding note in a pseudo-just tuning, thereby maximizing the consonance of that pseudo-harmonic timbre with notes of that pseudo-just tuning. == Partials, overtones, and harmonics == An overtone is any partial higher than the lowest partial in a compound tone. The relative strengths and frequency relationships of the component partials determine the timbre of an instrument. The similarity between the terms overtone and partial sometimes leads to their being loosely used interchangeably in a musical context, but they are counted differently, leading to some possible confusion. In the special case of instrumental timbres whose component partials closely match a harmonic series (such as with most strings and winds) rather than being inharmonic partials (such as with most pitched percussion instruments), it is also convenient to call the component partials "harmonics", but not strictly correct, because harmonics are numbered the same even when missing, while partials and overtones are only counted when present. This chart demonstrates how the three types of names (partial, overtone, and harmonic) are counted (assuming that the harmonics are present): In many musical instruments, it is possible to play the upper harmonics without the fundamental note being present. In a simple case (e.g., recorder) this has the effect of making the note go up in pitch by an octave, but in more complex cases many other pitch variations are obtained. In some cases it also changes the timbre of the note. This is part of the normal method of obtaining higher notes in wind instruments, where it is called overblowing. The extended technique of playing multiphonics also produces harmonics. On string instruments it is possible to produce very pure sounding notes, called harmonics or flageolets by string players, which have an eerie quality, as well as being high in pitch. Harmonics may be used to check at a unison the tuning of strings that are not tuned to the unison. For example, lightly fingering the node found halfway down the highest string of a cello produces the same pitch as lightly fingering the node ⁠ 1 / 3 ⁠ of the way down the second highest string. For the human voice see Overtone singing, which uses harmonics. While it is true that electronically produced periodic tones (e.g. square waves or other non-sinusoidal waves) have "harmonics" that are whole number multiples of the fundamental frequency, practical instruments do not all have this characteristic. For example, higher "harmonics" of piano notes are not true harmonics but are "overtones" and can be very sharp, i.e. a higher frequency than given by a pure harmonic series. This is especially true of instruments other than strings, brass, or woodwinds. Examples of these "other" instruments are xylophones, drums, bells, chimes, etc.; not all of their overtone frequencies make a simple whole number ratio with the fundamental frequency. (The fundamental frequency is the reciprocal of the longest time period of the collection of vibrations in some single periodic phenomenon.) == On stringed instruments == Harmonics may be singly produced [on stringed instruments] (1) by varying the point of contact with the bow, or (2) by slightly pressing the string at the nodes, or divisions of its aliquot parts ( 1 2 {\displaystyle {\tfrac {1}{2}}} , 1

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  • Decision tree pruning

    Decision tree pruning

    Pruning is a data compression technique in machine learning and search algorithms that reduces the size of decision trees by removing sections of the tree that are non-critical and redundant to classify instances. Pruning reduces the complexity of the final classifier, and hence improves predictive accuracy by the reduction of overfitting. One of the questions that arises in a decision tree algorithm is the optimal size of the final tree. A tree that is too large risks overfitting the training data and poorly generalizing to new samples. A small tree might not capture important structural information about the sample space. However, it is hard to tell when a tree algorithm should stop because it is impossible to tell if the addition of a single extra node will dramatically decrease error. This problem is known as the horizon effect. A common strategy is to grow the tree until each node contains a small number of instances then use pruning to remove nodes that do not provide additional information. Pruning should reduce the size of a learning tree without reducing predictive accuracy as measured by a cross-validation set. There are many techniques for tree pruning that differ in the measurement that is used to optimize performance. == Techniques == Pruning processes can be divided into two types (pre- and post-pruning). Pre-pruning procedures prevent a complete induction of the training set by replacing a stop () criterion in the induction algorithm (e.g. max. Tree depth or information gain (Attr)> minGain). Pre-pruning methods are considered to be more efficient because they do not induce an entire set, but rather trees remain small from the start. Prepruning methods share a common problem, the horizon effect. This is to be understood as the undesired premature termination of the induction by the stop () criterion. Post-pruning (or just pruning) is the most common way of simplifying trees. Here, nodes and subtrees are replaced with leaves to reduce complexity. Pruning can not only significantly reduce the size but also improve the classification accuracy of unseen objects. It may be the case that the accuracy of the assignment on the train set deteriorates, but the accuracy of the classification properties of the tree increases overall. The procedures are differentiated on the basis of their approach in the tree (top-down or bottom-up). === Bottom-up pruning === These procedures start at the last node in the tree (the lowest point). Following recursively upwards, they determine the relevance of each individual node. If the relevance for the classification is not given, the node is dropped or replaced by a leaf. The advantage is that no relevant sub-trees can be lost with this method. These methods include Reduced Error Pruning (REP), Minimum Cost Complexity Pruning (MCCP), or Minimum Error Pruning (MEP). === Top-down pruning === In contrast to the bottom-up method, this method starts at the root of the tree. Following the structure below, a relevance check is carried out which decides whether a node is relevant for the classification of all n items or not. By pruning the tree at an inner node, it can happen that an entire sub-tree (regardless of its relevance) is dropped. One of these representatives is pessimistic error pruning (PEP), which brings quite good results with unseen items. == Pruning algorithms == === Reduced error pruning === One of the simplest forms of pruning is reduced error pruning. Starting at the leaves, each node is replaced with its most popular class. If the prediction accuracy is not affected then the change is kept. While somewhat naive, reduced error pruning has the advantage of simplicity and speed. === Cost complexity pruning === Cost complexity pruning generates a series of trees ⁠ T 0 … T m {\displaystyle T_{0}\dots T_{m}} ⁠ where ⁠ T 0 {\displaystyle T_{0}} ⁠ is the initial tree and ⁠ T m {\displaystyle T_{m}} ⁠ is the root alone. At step ⁠ i {\displaystyle i} ⁠, the tree is created by removing a subtree from tree ⁠ i − 1 {\displaystyle i-1} ⁠ and replacing it with a leaf node with value chosen as in the tree building algorithm. The subtree that is removed is chosen as follows: Define the error rate of tree ⁠ T {\displaystyle T} ⁠ over data set ⁠ S {\displaystyle S} ⁠ as ⁠ err ⁡ ( T , S ) {\displaystyle \operatorname {err} (T,S)} ⁠. The subtree t {\displaystyle t} that minimizes err ⁡ ( prune ⁡ ( T , t ) , S ) − err ⁡ ( T , S ) | leaves ⁡ ( T ) | − | leaves ⁡ ( prune ⁡ ( T , t ) ) | {\displaystyle {\frac {\operatorname {err} (\operatorname {prune} (T,t),S)-\operatorname {err} (T,S)}{\left\vert \operatorname {leaves} (T)\right\vert -\left\vert \operatorname {leaves} (\operatorname {prune} (T,t))\right\vert }}} is chosen for removal. The function ⁠ prune ⁡ ( T , t ) {\displaystyle \operatorname {prune} (T,t)} ⁠ defines the tree obtained by pruning the subtrees ⁠ t {\displaystyle t} ⁠ from the tree ⁠ T {\displaystyle T} ⁠. Once the series of trees has been created, the best tree is chosen by generalized accuracy as measured by a training set or cross-validation. == Examples == Pruning could be applied in a compression scheme of a learning algorithm to remove the redundant details without compromising the model's performances. In neural networks, pruning removes entire neurons or layers of neurons.

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  • Web content development

    Web content development

    Web content development is the process of researching, writing, gathering, organizing, and editing information for publication on websites. Website content may consist of prose, graphics, pictures, recordings, movies, or other digital assets that could be distributed by a hypertext transfer protocol server, and viewed by a web browser. == Web developers and content developers == When the World Wide Web began, web developers either developed online content themselves, or modified existing documents and coded them into hypertext markup language (HTML). In time, the field of website development came to encompass many technologies, so it became difficult for website developers to maintain so many different skills. Content developers are specialized website developers who have content generation skills such as graphic design, multimedia development, professional writing, and documentation. They can integrate content into new or existing websites without using information technology skills such as script language programming and database programming. Content developers or technical content developers can also be technical writers who produce technical documentation that helps people understand and use a product or service. This documentation includes online help, manuals, white papers, design specifications, developer guides, deployment guides, release notes, etc. == Search engine optimization == Content developers may also be search engine optimization specialists, or internet marketing professionals. High quality, unique content is what search engines are looking for. Content development specialists, therefore, have a very important role to play in the search engine optimization process. One issue currently plaguing the world of web content development is keyword-stuffed content which are prepared solely for the purpose of manipulating search engine rankings. The effect is that content is written to appeal to search engine (algorithms) rather than human readers. Search engine optimization specialists commonly submit content to article directories to build their website's authority on any given topic. Most article directories allow visitors to republish submitted content with the agreement that all links are maintained. This has become a method of search engine optimization for many websites today. If written according to SEO copywriting rules, the submitted content will bring benefits to the publisher (free SEO-friendly content for a webpage) as well as to the author (a hyperlink pointing to his/her website, placed on an SEO-friendly webpage). == New content types == Web content is no longer restricted to text. Search engines now index audio/visual media, including video, images, PDFs, and other elements of a web page. Website owners sometimes use content protection networks to scan for plagiarized content.

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  • W3C Device Description Working Group

    W3C Device Description Working Group

    The W3C Device Description Working Group (DDWG), operating as part of the World Wide Web Consortium (W3C) Mobile Web Initiative (MWI), was chartered to "foster the provision and access to device descriptions that can be used in support of Web-enabled applications that provide an appropriate user experience on mobile devices." Mobile devices exhibit the greatest diversity of capabilities, and therefore present the greatest challenge to content adaptation technologies. The group published several documents, including a list of requirements for an interface to a Device Description Repository (DDR) and a standard interface meeting those requirements. The group was rechartered in 2006 to work in public towards the development of the Application Programming Interface (API) for a DDR. Early in 2007, the group launched a wiki and a blog to add to the public mailing list. The group subsequently published a formal vocabulary of core device properties, and an API called the DDR Simple API, which became a W3C Recommendation in December 2008. The group closed at the end of 2008, but with the intention of maintaining the Web pages, blog and wiki through W3C volunteer effort. == Publications == The DDWG published several W3C Working Group Notes and one W3C Recommendation. A W3C WG Note that articulates what the W3C and other organizations are doing or have already done with regard to device information. This document suggests an environment in which these technologies work together to meet the goals of content adaptation. The completed document was published on 31 October 2007. A W3C WG Note describing the ecosystem surrounding creation, maintenance and use of device descriptions. The completed document was published on 31 October 2007. A W3C WG Note describing a set of requirements for a reference repository of device descriptions. The completed document was published on 17 December 2007. A W3C WG Note describing a process to manage contributions to an initial core vocabulary, identification of key device properties, a formal initial core vocabulary and the identification of a maintainer for the core vocabulary. The details were contained in the Working Group Note describing the DDWG Core Vocabulary published on 14 April 2008. A W3C WG Note defining useful grouping and structure patterns in device descriptions. The Device Description Structures document was published as a Working Draft on 5 December 2008. The intention is that this document will be future input to other W3C groups. A W3C Recommendation defining a language-neutral programming interface to a Device Description Repository. The DDR Simple API was published on 5 December 2008. There is the possibility of future publications on the DDWG wiki describing implementations of the API in various languages, including Java, IDL, WSDL, C# etc. Much of the DDWG's material was developed in public via the DDWG Wiki and through their public mailing lists.

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