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National Repository of Grey Literature 23 records found  beginprevious21 - 23  jump to record: Search took 0.01 seconds. 
Classification and Regression Forests
 Klaschka, Jan ; Kotrč, Emil
Classification forest is a classification model constructed by combinaning several classification trees. A predictor vector is assigned a class by each of the trees, and the overall classification function is given by majority voting. Similarly, a regression forest consists of several regression trees, and the overall regression function is defined as a weighted average of regression functions of individual trees. Brief explanations of some forest construction methods, namely of bagging, boosting, arcing and Random Forests, are given.
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Classification and Regression Forests.
 Klaschka, Jan ; Kotrč, Emil
Classification forest is a classification model constructed by combinaning several classification trees. A predictor vector is assigned a class by each of the trees, and the overall classification function is given by majority voting. Similarly, a regression forest consists of several regression trees, and the overall regression function is defined as a weighted average of regression functions of individual trees. Brief explanations of some forest construction methods, namely of bagging, boosting, arcing and Random Forests, are given.
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Leaf Confidences for Random Forest
 Kotrč, Emil
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National Repository of Grey Literature : 23 records found   beginprevious21 - 23  jump to record:
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