<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><channel rdf:about="https://www.bibsonomy.org/tag/supervised"><title>BibSonomy bookmarks for /tag/supervised</title><link>https://www.bibsonomy.org/tag/supervised</link><description>BibSonomy RSS Feed for /tag/supervised</description><items><rdf:Seq><rdf:li rdf:resource="https://www.topweightloss.io/medvi-vs-wellmedr"/><rdf:li rdf:resource="https://utubeparents.com"/><rdf:li rdf:resource="https://utubeparents.com"/><rdf:li rdf:resource="https://link.springer.com/article/10.1007/s11192-018-2797-4"/><rdf:li rdf:resource="https://machinelearningmastery.com/get-your-hands-dirty-with-scikit-learn-now/"/><rdf:li rdf:resource="http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian%3Aen-US%3Aunofficial&amp;q=hyperspectral+supervised+matlab&amp;aq=f&amp;oq=&amp;aqi="/><rdf:li rdf:resource="http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian%3Aen-US%3Aunofficial&amp;q=hyperspectral+supervised+python&amp;aq=f&amp;oq=&amp;aqi="/><rdf:li rdf:resource="http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian:en-US:unofficial&amp;ei=YRc4StvYDYniswPDyZj-Bg&amp;sa=X&amp;oi=spell&amp;resnum=0&amp;ct=result&amp;cd=1&amp;q=%22open+source%22+hyperspectral+supervised&amp;spell=1"/><rdf:li rdf:resource="http://www.slideshare.net/mattspitz/practical-machine-learning-in-python"/><rdf:li rdf:resource="https://shuyo.wordpress.com/2013/07/24/python-implementation-of-labeled-lda-ramage-emnlp2009/"/><rdf:li rdf:resource="https://github.com/blei-lab/class-slda"/><rdf:li rdf:resource="http://anton.dnsalias.org/public/tobias/publications/anton-lwa05.pdf"/><rdf:li rdf:resource="http://anton.dnsalias.org/public/tobias/publications/anton-thesis03.pdf"/></rdf:Seq></items></channel><item rdf:about="https://www.topweightloss.io/medvi-vs-wellmedr"><title>Compare the Best Medically Supervised Weight Loss Providers Online</title><description>Compare best medically supervised weight loss providers online based on clinical support, medication options, pricing, and convenience. topweightloss.io helps readers evaluate different services and understand which provider features may better suit their individual weight management preferences and goals.</description><link>https://www.topweightloss.io/medvi-vs-wellmedr</link><dc:creator>topweightloss</dc:creator><dc:date>2026-08-10T14:50:54+02:00</dc:date><dc:subject>best loss medically online providers supervised weight </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Compare best medically supervised weight loss providers online based on clinical support, medication options, pricing, and convenience. topweightloss.io helps readers evaluate different services and understand which provider features may better suit their individual weight management preferences and goals.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/best"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/loss"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/medically"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/online"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/providers"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/weight"/></rdf:Bag></taxo:topics></item><item rdf:about="https://utubeparents.com"><title>Complete Guide to YouTube Parental Controls: Restricted Mode, Supervised Accounts &amp; YouTube Kids</title><description>YouTube has become the go-to video platform for kids of all ages, but with millions of hours of content uploaded every day, parents need to be proactive about safety. Setting up proper YouTube parental controls is essential for creating a safe viewing environment for children. This guide covers everything you need to know about YouTube safety settings and how to implement them effectively.

Understanding YouTube&#039;s Built-in Parental Controls

YouTube offers several layers of protection that parents can activate. The most basic is Restricted Mode, which uses automated filters to screen out potentially mature content. You can enable Restricted Mode at the browser level on computers or within the app on mobile devices. While not perfect, it provides a first line of defense against inappropriate videos. To activate it, click your profile icon, scroll to the bottom of the menu, and toggle Restricted Mode on.

Supervised Accounts: The Middle Ground

For parents who want more control than Restricted Mode but aren&#039;t ready for YouTube Kids, supervised accounts offer a balanced solution. Available through Google Family Link, supervised accounts let you choose from three content settings: Explore (ages 9+), Explore More (ages 13+), and Most of YouTube (older teens). Each level unlocks progressively more content while still blocking age-restricted material. You can also monitor watch history and block specific channels.

YouTube Kids vs Regular YouTube

YouTube Kids is a separate app designed specifically for children under 13. It features a simpler interface, curated content from approved partners, and robust parental controls including timer settings, search disabling, and content level selection by age group (Preschool, Younger, Older). However, YouTube Kids has faced criticism because some inappropriate content occasionally slips through algorithmic filters. The regular YouTube app with supervised accounts may actually provide better oversight for older children since parents can review exactly what their kids watch.

Third-Party Monitoring Tools

For parents who want additional protection beyond what YouTube offers, several third-party monitoring tools are available. Apps like Bark, Qustodio, and Norton Family provide cross-platform monitoring that includes YouTube activity tracking, screen time management, and detailed reports. These tools can alert parents to concerning content across multiple platforms, not just YouTube.

For a comprehensive resource on parental controls for YouTube and other platforms, visit https://utubeparents.com which offers detailed guides and up-to-date information about YouTube safety settings. The site covers everything from basic setup to advanced monitoring strategies for concerned parents.

Remember that no technological solution replaces active parental involvement. Talk to your children about what they watch, watch videos together when possible, and keep communication open about online safety. The best YouTube parental controls combine technical tools with ongoing conversations about digital citizenship.</description><link>https://utubeparents.com</link><dc:creator>utubeparent</dc:creator><dc:date>2026-08-04T13:29:56+02:00</dc:date><dc:subject>accounts controls kids mode monitoring parental restricted safety supervised youtube </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;YouTube has become the go-to video platform for kids of all ages, but with millions of hours of content uploaded every day, parents need to be proactive about safety. Setting up proper YouTube parental controls is essential for creating a safe viewing environment for children. This guide covers everything you need to know about YouTube safety settings and how to implement them effectively.

Understanding YouTube&amp;#039;s Built-in Parental Controls

YouTube offers several layers of protection that parents can activate. The most basic is Restricted Mode, which uses automated filters to screen out potentially mature content. You can enable Restricted Mode at the browser level on computers or within the app on mobile devices. While not perfect, it provides a first line of defense against inappropriate videos. To activate it, click your profile icon, scroll to the bottom of the menu, and toggle Restricted Mode on.

Supervised Accounts: The Middle Ground

For parents who want more control than Restricted Mode but aren&amp;#039;t ready for YouTube Kids, supervised accounts offer a balanced solution. Available through Google Family Link, supervised accounts let you choose from three content settings: Explore (ages 9+), Explore More (ages 13+), and Most of YouTube (older teens). Each level unlocks progressively more content while still blocking age-restricted material. You can also monitor watch history and block specific channels.

YouTube Kids vs Regular YouTube

YouTube Kids is a separate app designed specifically for children under 13. It features a simpler interface, curated content from approved partners, and robust parental controls including timer settings, search disabling, and content level selection by age group (Preschool, Younger, Older). However, YouTube Kids has faced criticism because some inappropriate content occasionally slips through algorithmic filters. The regular YouTube app with supervised accounts may actually provide better oversight for older children since parents can review exactly what their kids watch.

Third-Party Monitoring Tools

For parents who want additional protection beyond what YouTube offers, several third-party monitoring tools are available. Apps like Bark, Qustodio, and Norton Family provide cross-platform monitoring that includes YouTube activity tracking, screen time management, and detailed reports. These tools can alert parents to concerning content across multiple platforms, not just YouTube.

For a comprehensive resource on parental controls for YouTube and other platforms, visit https://utubeparents.com which offers detailed guides and up-to-date information about YouTube safety settings. The site covers everything from basic setup to advanced monitoring strategies for concerned parents.

Remember that no technological solution replaces active parental involvement. Talk to your children about what they watch, watch videos together when possible, and keep communication open about online safety. The best YouTube parental controls combine technical tools with ongoing conversations about digital citizenship.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/accounts"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/controls"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/kids"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/mode"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/monitoring"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/parental"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/restricted"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/safety"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/youtube"/></rdf:Bag></taxo:topics></item><item rdf:about="https://utubeparents.com"><title>YouTube Kids vs YouTube: The Complete Parental Control Guide for 2024</title><description>YouTube Kids vs YouTube: Which Is Right for Your Child?

As a parent in the digital age, deciding between YouTube Kids and regular YouTube for your children can feel overwhelming. Both platforms offer vast libraries of content, but they differ dramatically in safety features, content curation, and age-appropriateness. This comprehensive guide breaks down everything you need to know about the YouTube Kids vs YouTube debate.

What Is YouTube Kids?

YouTube Kids is a dedicated app designed specifically for children, offering a curated, walled-garden experience. The app filters content into three age categories: Preschool (ages 4 and under), Younger (ages 5-8), and Older (ages 9-12). Every video on the platform goes through automated filtering and human review to ensure it meets child-appropriate standards.

Key features of YouTube Kids include built-in parental controls, timer settings that let you limit screen time, the ability to block specific videos or channels, and an option to disable the search function entirely. This makes the YouTube Kids comparison particularly favorable for parents who want a worry-free experience.

What Is Regular YouTube with Supervised Accounts?

In 2021, YouTube introduced supervised accounts as a middle ground. This feature allows parents to set content restrictions on the main YouTube platform using three tiers: Explore (ages 9+), Explore More (ages 13+), and Most of YouTube (everything except age-restricted content). Unlike YouTube Kids, supervised accounts still use the standard YouTube interface.

Key Differences: YouTube Kids vs Regular YouTube

Content Filtering: YouTube Kids uses a highly restrictive algorithm combined with human review. Regular YouTube relies on community flagging and automated systems, which can miss inappropriate content. The YouTube Kids comparison clearly shows superior safety features.

Ads and Commercial Content: YouTube Kids has stricter policies on advertising. Paid product placements and endorsements are not allowed, and ads are clearly labeled. Regular YouTube has fewer restrictions, making YouTube Kids the best YouTube option for kids when it comes to limiting commercial exposure.

Comments and Social Features: YouTube Kids disables comments entirely. Regular YouTube with supervised accounts may allow comments depending on the content tier. This is a crucial consideration in the YouTube Kids vs YouTube analysis.

Search Functionality: Parents can disable search in YouTube Kids, limiting children to pre-approved content only. Regular YouTube always has search enabled, though restricted mode can help.

Content Variety: Regular YouTube offers significantly more content. YouTube Kids has a more limited library, which some parents see as a feature rather than a limitation.

Managing Both Platforms from One Dashboard

Google Family Link serves as the unified dashboard for managing both YouTube Kids and regular YouTube supervised accounts. Through Family Link, parents can set screen time limits, approve or block apps, manage content restrictions, and view activity reports all in one place. This centralized management is essential for households where different children use different platforms.

Which Should You Choose?

For children under 9, YouTube Kids is generally the safer choice. The curated environment, disabled comments, and stricter ad policies create a more controlled experience. For preteens and teenagers, supervised accounts on regular YouTube provide more freedom while maintaining guardrails.

For a deeper dive into parental control strategies and platform comparisons, visit YouTube Kids vs YouTube at utubeparents.com where you will find detailed reviews, setup tutorials, and the latest updates on family safety features. Making the right choice between YouTube Kids and regular YouTube starts with understanding what each platform offers.</description><link>https://utubeparents.com</link><dc:creator>utubeparents</dc:creator><dc:date>2026-08-04T01:16:54+02:00</dc:date><dc:subject>accounts comparison content controls family kids parental safety screen supervised time youtube </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;YouTube Kids vs YouTube: Which Is Right for Your Child?

As a parent in the digital age, deciding between YouTube Kids and regular YouTube for your children can feel overwhelming. Both platforms offer vast libraries of content, but they differ dramatically in safety features, content curation, and age-appropriateness. This comprehensive guide breaks down everything you need to know about the YouTube Kids vs YouTube debate.

What Is YouTube Kids?

YouTube Kids is a dedicated app designed specifically for children, offering a curated, walled-garden experience. The app filters content into three age categories: Preschool (ages 4 and under), Younger (ages 5-8), and Older (ages 9-12). Every video on the platform goes through automated filtering and human review to ensure it meets child-appropriate standards.

Key features of YouTube Kids include built-in parental controls, timer settings that let you limit screen time, the ability to block specific videos or channels, and an option to disable the search function entirely. This makes the YouTube Kids comparison particularly favorable for parents who want a worry-free experience.

What Is Regular YouTube with Supervised Accounts?

In 2021, YouTube introduced supervised accounts as a middle ground. This feature allows parents to set content restrictions on the main YouTube platform using three tiers: Explore (ages 9+), Explore More (ages 13+), and Most of YouTube (everything except age-restricted content). Unlike YouTube Kids, supervised accounts still use the standard YouTube interface.

Key Differences: YouTube Kids vs Regular YouTube

Content Filtering: YouTube Kids uses a highly restrictive algorithm combined with human review. Regular YouTube relies on community flagging and automated systems, which can miss inappropriate content. The YouTube Kids comparison clearly shows superior safety features.

Ads and Commercial Content: YouTube Kids has stricter policies on advertising. Paid product placements and endorsements are not allowed, and ads are clearly labeled. Regular YouTube has fewer restrictions, making YouTube Kids the best YouTube option for kids when it comes to limiting commercial exposure.

Comments and Social Features: YouTube Kids disables comments entirely. Regular YouTube with supervised accounts may allow comments depending on the content tier. This is a crucial consideration in the YouTube Kids vs YouTube analysis.

Search Functionality: Parents can disable search in YouTube Kids, limiting children to pre-approved content only. Regular YouTube always has search enabled, though restricted mode can help.

Content Variety: Regular YouTube offers significantly more content. YouTube Kids has a more limited library, which some parents see as a feature rather than a limitation.

Managing Both Platforms from One Dashboard

Google Family Link serves as the unified dashboard for managing both YouTube Kids and regular YouTube supervised accounts. Through Family Link, parents can set screen time limits, approve or block apps, manage content restrictions, and view activity reports all in one place. This centralized management is essential for households where different children use different platforms.

Which Should You Choose?

For children under 9, YouTube Kids is generally the safer choice. The curated environment, disabled comments, and stricter ad policies create a more controlled experience. For preteens and teenagers, supervised accounts on regular YouTube provide more freedom while maintaining guardrails.

For a deeper dive into parental control strategies and platform comparisons, visit YouTube Kids vs YouTube at utubeparents.com where you will find detailed reviews, setup tutorials, and the latest updates on family safety features. Making the right choice between YouTube Kids and regular YouTube starts with understanding what each platform offers.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/accounts"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/comparison"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/content"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/controls"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/family"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/kids"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/parental"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/safety"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/screen"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/time"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/youtube"/></rdf:Bag></taxo:topics></item><item rdf:about="https://link.springer.com/article/10.1007/s11192-018-2797-4"><title>Identifying named entities in academic biographies with supervised learning | SpringerLink</title><description>Personal webpages of researchers or faculty members make up a percentage of the academic web. These webpages contain semi-structured or plain text information, and research has shown the importance...</description><link>https://link.springer.com/article/10.1007/s11192-018-2797-4</link><dc:creator>parismic</dc:creator><dc:date>2019-11-27T21:28:55+01:00</dc:date><dc:subject>bio entity identifying named page supervised web </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Personal webpages of researchers or faculty members make up a percentage of the academic web. These webpages contain semi-structured or plain text information, and research has shown the importance...&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bio"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/entity"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/identifying"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/named"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/page"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/web"/></rdf:Bag></taxo:topics></item><item rdf:about="https://machinelearningmastery.com/get-your-hands-dirty-with-scikit-learn-now/"><title>Machine Learning Algorithm Recipes in scikit-learn</title><description>In this post you will see 5 recipes of supervised classification algorithms applied to small standard datasets that are provided with the scikit-learn library.</description><link>https://machinelearningmastery.com/get-your-hands-dirty-with-scikit-learn-now/</link><dc:creator>schwemmlein</dc:creator><dc:date>2017-10-15T13:14:24+02:00</dc:date><dc:subject>algorithm classification python scikit scikit-learn supervised </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;In this post you will see 5 recipes of supervised classification algorithms applied to small standard datasets that are provided with the scikit-learn library.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/algorithm"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/classification"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/python"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/scikit"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/scikit-learn"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian%3Aen-US%3Aunofficial&amp;q=hyperspectral+supervised+matlab&amp;aq=f&amp;oq=&amp;aqi="><title>hyperspectral supervised matlab - Google Search</title><description></description><link>http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian%3Aen-US%3Aunofficial&amp;q=hyperspectral+supervised+matlab&amp;aq=f&amp;oq=&amp;aqi=</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:00:57+01:00</dc:date><dc:subject>hyperspectral supervised matlab work todo+++ </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:00:57+01:00&#034; href=&#034;http://www.google.com/search?hl=en&amp;amp;client=iceweasel-a&amp;amp;rls=org.debian%3Aen-US%3Aunofficial&amp;amp;q=hyperspectral+supervised+matlab&amp;amp;aq=f&amp;amp;oq=&amp;amp;aqi=&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.google.com/search?hl=en&amp;amp;client=iceweasel-a&amp;amp;rls=org.debian%3Aen-US%3Aunofficial&amp;amp;q=hyperspectral+supervised+matlab&amp;amp;aq=f&amp;amp;oq=&amp;amp;aqi=&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/hyperspectral"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/matlab"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/work"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/todo+++"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian%3Aen-US%3Aunofficial&amp;q=hyperspectral+supervised+python&amp;aq=f&amp;oq=&amp;aqi="><title>hyperspectral supervised python - Google Search</title><description></description><link>http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian%3Aen-US%3Aunofficial&amp;q=hyperspectral+supervised+python&amp;aq=f&amp;oq=&amp;aqi=</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:00:57+01:00</dc:date><dc:subject>hyperspectral supervised python work todo+++ </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:00:57+01:00&#034; href=&#034;http://www.google.com/search?hl=en&amp;amp;client=iceweasel-a&amp;amp;rls=org.debian%3Aen-US%3Aunofficial&amp;amp;q=hyperspectral+supervised+python&amp;amp;aq=f&amp;amp;oq=&amp;amp;aqi=&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.google.com/search?hl=en&amp;amp;client=iceweasel-a&amp;amp;rls=org.debian%3Aen-US%3Aunofficial&amp;amp;q=hyperspectral+supervised+python&amp;amp;aq=f&amp;amp;oq=&amp;amp;aqi=&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/hyperspectral"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/python"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/work"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/todo+++"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian:en-US:unofficial&amp;ei=YRc4StvYDYniswPDyZj-Bg&amp;sa=X&amp;oi=spell&amp;resnum=0&amp;ct=result&amp;cd=1&amp;q=%22open+source%22+hyperspectral+supervised&amp;spell=1"><title>&#034;open source&#034; hyperspectral supervised - Google Search</title><description></description><link>http://www.google.com/search?hl=en&amp;client=iceweasel-a&amp;rls=org.debian:en-US:unofficial&amp;ei=YRc4StvYDYniswPDyZj-Bg&amp;sa=X&amp;oi=spell&amp;resnum=0&amp;ct=result&amp;cd=1&amp;q=%22open+source%22+hyperspectral+supervised&amp;spell=1</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:00:57+01:00</dc:date><dc:subject>foss hyperspectral supervised work todo+++ </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:00:57+01:00&#034; href=&#034;http://www.google.com/search?hl=en&amp;amp;client=iceweasel-a&amp;amp;rls=org.debian:en-US:unofficial&amp;amp;ei=YRc4StvYDYniswPDyZj-Bg&amp;amp;sa=X&amp;amp;oi=spell&amp;amp;resnum=0&amp;amp;ct=result&amp;amp;cd=1&amp;amp;q=%22open+source%22+hyperspectral+supervised&amp;amp;spell=1&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.google.com/search?hl=en&amp;amp;client=iceweasel-a&amp;amp;rls=org.debian:en-US:unofficial&amp;amp;ei=YRc4StvYDYniswPDyZj-Bg&amp;amp;sa=X&amp;amp;oi=spell&amp;amp;resnum=0&amp;amp;ct=result&amp;amp;cd=1&amp;amp;q=%22open+source%22+hyperspectral+supervised&amp;amp;spell=1&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/foss"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/hyperspectral"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/work"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/todo+++"/></rdf:Bag></taxo:topics></item><item rdf:about="http://www.slideshare.net/mattspitz/practical-machine-learning-in-python"><title>Practical Machine Learning in Python</title><description></description><link>http://www.slideshare.net/mattspitz/practical-machine-learning-in-python</link><dc:creator>bshanks</dc:creator><dc:date>2016-12-12T10:00:27+01:00</dc:date><dc:subject>top list python lib ml slide intro supervised </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-12-12T10:00:27+01:00&#034; href=&#034;http://www.slideshare.net/mattspitz/practical-machine-learning-in-python&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;http://www.slideshare.net/mattspitz/practical-machine-learning-in-python&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/top"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/list"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/python"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/lib"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/ml"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/slide"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/intro"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/></rdf:Bag></taxo:topics></item><item rdf:about="https://shuyo.wordpress.com/2013/07/24/python-implementation-of-labeled-lda-ramage-emnlp2009/"><title>Python implementation of Labeled LDA (Ramage+ EMNLP2009) | Shuyo&#039;s Weblog</title><description></description><link>https://shuyo.wordpress.com/2013/07/24/python-implementation-of-labeled-lda-ramage-emnlp2009/</link><dc:creator>ans</dc:creator><dc:date>2016-05-17T11:56:52+02:00</dc:date><dc:subject>lda python supervised </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-05-17T11:56:52+02:00&#034; href=&#034;https://shuyo.wordpress.com/2013/07/24/python-implementation-of-labeled-lda-ramage-emnlp2009/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://shuyo.wordpress.com/2013/07/24/python-implementation-of-labeled-lda-ramage-emnlp2009/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/lda"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/python"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/></rdf:Bag></taxo:topics></item><item rdf:about="https://github.com/blei-lab/class-slda"><title>GitHub - blei-lab/class-slda: Implements supervised topic models with a categorical response.</title><description></description><link>https://github.com/blei-lab/class-slda</link><dc:creator>ans</dc:creator><dc:date>2016-05-17T11:55:57+02:00</dc:date><dc:subject>lda modelling supervised topic </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2016-05-17T11:55:57+02:00&#034; href=&#034;https://github.com/blei-lab/class-slda&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://github.com/blei-lab/class-slda&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/lda"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/modelling"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/topic"/></rdf:Bag></taxo:topics></item><item rdf:about="http://anton.dnsalias.org/public/tobias/publications/anton-lwa05.pdf"><title>XPath-Wrapper induction by generalizing tree traversal patterns</title><description>A version space algorithm for learning extracting rules from tree-structured documents. Resulting hypotheses are called &#034;tag tree patterns&#034;. A Mapping from tag tree patterns to statements in the XPath language is defined.
</description><link>http://anton.dnsalias.org/public/tobias/publications/anton-lwa05.pdf</link><dc:creator>tobias</dc:creator><dc:date>2006-07-03T08:45:04+02:00</dc:date><dc:subject>induction, Wrapper XPath supervised machine learning, </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;A version space algorithm for learning extracting rules from tree-structured documents. Resulting hypotheses are called &amp;#034;tag tree patterns&amp;#034;. A Mapping from tag tree patterns to statements in the XPath language is defined.
&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/induction,"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Wrapper"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/XPath"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/machine"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learning,"/></rdf:Bag></taxo:topics></item><item rdf:about="http://anton.dnsalias.org/public/tobias/publications/anton-thesis03.pdf"><title>Halbautomatische Erzeugung von HTML-Wrappern</title><description>Diplomarbeit Tobias Anton</description><link>http://anton.dnsalias.org/public/tobias/publications/anton-thesis03.pdf</link><dc:creator>tobias</dc:creator><dc:date>2006-07-03T08:30:32+02:00</dc:date><dc:subject>induction, learning Wrapper Computer Science, Diplomarbeit, thesis, supervised Informatik, machine learning, </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Diplomarbeit Tobias Anton&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/induction,"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learning"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Wrapper"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Computer"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Science,"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Diplomarbeit,"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/thesis,"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/supervised"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Informatik,"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/machine"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/learning,"/></rdf:Bag></taxo:topics></item></rdf:RDF>