Many scientific problems entail labeling data items with one of a given, finite set of classes based on features of the data items. For example, oncologists classify tumors as different known ...

Decision trees are a simple but powerful prediction method ... the cost of misclassification if this varies among classes. For example, in classifying cancer cases it may be more costly to ...

Decision trees are useful for relatively small datasets and when the trained model must be easily interpretable. And scikit decision trees are very easy to implement. The two main downsides to ...

The concepts underlying decision tree regression are relatively simple, but implementation is tricky ... the data to other regression algorithms that require normalization (for example, k-nearest ...