Search Results

4 results for “decision tree”

Formulae (4)

Gini = 1 - \sum_{i=1}^{n} p_i^2

Probability of misclassifying a random element; used in decision trees.

H(S) = -\sum_i p_i \log_2 p_i

Measures impurity/uncertainty of a set; used to split decision trees.

G = 1 - \sum_i p_i^2

Probability of misclassifying a random sample; the default split metric in CART trees.

IG = H(S) - \sum_k \dfrac{|S_k|}{|S|}H(S_k)

Reduction in entropy achieved by splitting a node on a feature.