Random Forest Classifiers
نویسنده
چکیده
A classification tree represents the probability spaceP of posterior probabilities p(y|x) of label given feature by a recursive partition of the feature space X , where each partition is performed by a test on the feature x called a split rule. To each set of the partition is assigned a posterior probability distribution, and p(y|x) for a feature x ∈ X is then defined as the probability distribution associated with the set of the partition that contains x. A popular split rule called a 1-rule partitions a set S ⊆ X × Y into the two sets
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