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OpenCV Essentials by Jesus Salido Tercero, Julio Alberto Patón Incertis, Ismael Serrano Gracia, Gloria Bueno García, Noelia Vállez Enano, Mª del Milagro Fernández Carrobles, Oscar Deniz Suarez

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The Random Forest classifier

Random Forests are a general class of ensemble building methods that use a decision tree as the base classifier. The Random Forest classifier is a variation of the Bagging classifier (Bootstrap Aggregating). The Bagging algorithm is a method of classification that generates weak individual classifiers using bootstrap. Each classifier is trained on a random redistribution of the training set so that many of the original examples may be repeated in each classification.

The principal difference between Bagging and Random Forest is that Bagging uses all the features in each tree node and Random Forest selects a random subset of the features. The suitable number of randomized features corresponds to the square root of the ...

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