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Ensemble Machine Learning by Ankit Dixit

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What is the difference?

The basic and the most important difference between a classification and a regression tree is their output value. While for classification trees, the output values are always discrete or categorical in nature, the output of the regression trees is always a continuous value. One of the most important differences between them is an evaluation of the splits. While we used Gini index and Shannon entropy to evaluate splits in case of classification trees, regression trees use some loss functions to do this; the most popular loss is the sum of squares. There are many more differences between the two; we will see them during our progress. The following is the figure that describes the use cases of different tree algorithms: ...

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