May 2019
Intermediate to advanced
162 pages
4h 24m
English
Content preview from Supervised Machine Learning with Python
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Classification tree
Let's go ahead and walk through a classification tree example. We will be using the information gain criteria. In PyCharm there are three scripts open, two of which are metrics.py and cart.py, both of which are found inside of the packtml/decision_tree submodule. Then we have the example_classification_decision_tree.py file, which is in examples/decision_tree. Let's start with metrics.
If you open up the cart.py file, we have an order in which we should step through this so that you can understand how the decision tree class is going to work:
# 1. metrics.InformationGain & metrics.VarianceReduction# 2. RandomSplitter# 3. LeafNode# 4. BaseCART
Starting with the metrics.py file from the top, you can see that _all_ is going ...
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