Expected error estimate

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expected error estimate

Laplace error estimate

In pruning a decision tree, one needs to be able to estimate the expected error at any node (branch or leaf). This can be done using the Laplace error estimate, which is given by the formula

E(S) = (Nn + k – 1) / (N + k).


S is the set of instances in a node
k is the number of classes (e.g. 2 if instances are just being classified into 2 classes: say positive and negative)
N is the is the number of instances in S
C is the majority class in S
n out of N examples in S belong to C

Source : INWS machine learning dictionary ]

Contributeurs : Pitpitt