From the course: Machine Learning and AI: Advanced Decision Trees with SPSS
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Costs and priors
From the course: Machine Learning and AI: Advanced Decision Trees with SPSS
Costs and priors
- [Instructor] Now I'd like to talk about costs. Now, costs are a feature that almost all the decision tree algorithms have, but I'm going to demonstrate them via CART, because CART has a really nice feature that some of the other algorithms doesn't have in regards to costs. I'm going to start by opening a stream that I've created for just this purpose. The first CART model that's been already placed on the stream here was run on default settings, so nothing particularly special about that model. Now, in the Settings for the CART modeling node, I'm going to show you where the settings for costs are, you can check off Use misclassification costs and I've increased the value in the upper right corner from the original 1.0 to 5.0. What's going on here? Well, that corner of the matrix means the following. Those are folks that actually died in the accident but the model said that they would survive. That's a particular kind of mistake. The opposite kind of mistake would be predicting that…
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Contents
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Ensembles4m 48s
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What is bagging?7m 19s
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Using bagging for feature selection3m 55s
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Random forests2m 57s
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What is boosting?3m 32s
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What is XGBoost?1m 55s
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XGBoost Tree node2m 56s
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Costs and priors5m 11s
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XGBoost Linear1m 50s
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