课程: Machine Learning and AI Foundations: Decision Trees with KNIME
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What is the Gini coefficient? - KNIME教程
课程: Machine Learning and AI Foundations: Decision Trees with KNIME
What is the Gini coefficient?
- [Instructor] When Breiman and his colleagues were developing classification trees, the method that they chose to form a branch utilizes what's called the Gini coefficient. You may have heard the name in a different context. Corrado Gini was an Italian statistician, demographer, and sociologist. The Gini coefficient was originally used to measure income inequality. And it's still used for that today. You may have seen maps color coded by the Gini coefficient. Here we're looking at a map of the United States showing the Gini index by county and you can see that the darker areas are the very large metropolitan areas. It looks like Boston, New York City, Miami, Los Angeles, San Francisco, among others. And it wouldn't be surprising that in very large cities, you might have extremes of wealth and lower income. Where you see the lighter colors, it looks like Utah, Northern Nevada, very rural areas, you seem to have a lot less…
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内容
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Introducing Leo Breiman and CART4 分钟 14 秒
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What is the Gini coefficient?2 分钟 57 秒
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How CART handles missing data using surrogates5 分钟 28 秒
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Changing the settings in KNIME2 分钟 50 秒
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How CART handles nominal variables1 分钟 45 秒
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A quick look at the complete CART tree2 分钟 26 秒
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Evaluating the accuracy of your CART tree1 分钟 37 秒
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