What does `sample_weight` do to the way a `DecisionTreeClassifier` works in sklearn?
Some quick preliminaries: Let’s say we have a classification problem with K classes. In a region of feature space represented by the node of a decision tree, recall that the “impurity” of the region is measured by quantifying the inhomogeneity, using the probability of the class in that region. Normally, we estimate: Pr(Class=k) = #(examples … Read more