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This package contains the default implementation of the decision tree algorithm.
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The decision tree algorithm supports:
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- + information loss calculation with entropy and gini for classification and variance for regression
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- + node model pruning
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- + printing to dot files
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- + unit tests
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+ + Binary classification
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+ + Regression
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+ + Information loss calculation with entropy and gini for classification and variance for regression
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+ + Both continuous and categorical features
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- #Performance testing
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+ # Tree improvements
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+ + Node model pruning
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+ + Printing to dot files
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- #Future Extensions
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+ # Future Ensemble Extensions
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+ Random forests
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+ Boosting
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- + Extremely randomized trees
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+ + Extremely randomized trees
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