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ENTROPY-BASED WEIGHTING IN RANDOM FOREST MODELS
ENTROPY-BASED WEIGHTING IN RANDOM FOREST MODELS
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机译:随机森林模型中基于熵的加权
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摘要
A weighting value is determined for each of a plurality of decision trees in a random forest model hosted on a particular device, where the weighting is based on entropy of the respective decision tree. A new decision tree is received at the particular device and a weighting value is determined for the new decision tree based on entropy of the new decision tree. Based on the determined weighting value, it is determined whether to add the new the decision tree to the random forest model. A classification for data generated at the particular device is predicted using the random forest model.
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