课程: Machine Learning and AI Foundations: Decision Trees with KNIME
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When to turn off pruning - KNIME教程
课程: Machine Learning and AI Foundations: Decision Trees with KNIME
When to turn off pruning
- [Instructor] Okay, we are in the same workflow. We've built our model, we've checked its accuracy. On one level, we're all done. But I want to talk about the effects of turning off pruning and actually demonstrate that. So let's take a look. So we go in and we have an opportunity to deselect Reduced Error Pruning. We're going to keep it on for just a little bit longer. I also want to mention that reduced error pruning is the type of pruning and C4.5. Classification trees has a different kind of pruning called cost complexity pruning. We're going to talk only about this kind, because it's supported in decision tree learner. We won't be demonstrating cost complexity pruning, 'cause it's not supported in the decision tree learner. So let's click on OK. And it's just reminding us that the settings weren't changed. That's fine, 'cause we're going to do a little exercise here. We're going to take a look at the decision tree,…
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内容
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Ross Quinlan, ID3, C4.5, and C5.02 分钟 37 秒
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Understanding the entropy calculation6 分钟 36 秒
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How C4.5 handles missing data3 分钟 5 秒
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The Give Me Some Credit data set2 分钟 58 秒
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Working with the prebuilt example5 分钟 30 秒
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KNIME settings for C4.53 分钟 10 秒
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How C4.5 handles nominal variables2 分钟 36 秒
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How C4.5 handles continuous variables1 分钟 46 秒
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Equal size sampling2 分钟 24 秒
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A quick look at the complete C4.5 tree2 分钟 45 秒
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Evaluating the accuracy of your C4.5 tree3 分钟 5 秒
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When to turn off pruning5 分钟 27 秒
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