What are the advantages of logistic regression over decision trees? originally appeared on ... It can make a huge difference how you represent your features to make one model perform better ...

All of the predictor values are between -1 and +1. There are 200 training/reference data items and 40 test items. When using decision tree regression, it's not necessary to normalize the training data ...

Decision trees, such as C4.5 (ref ... If I is the entropy function, then the difference between the entropy of the distribution of the classes in the parent node and this weighted average of ...

When using decision trees in a gradient boosting system for regression, it's not necessary to normalize ... The first tree [0] was trained to predict the residuals (differences) between the predicted ...