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随机森林算法的构造过程：1、通过给定的原始数据，选出其中部分数据进行决策树的构造，数据选取是”有放回“的过程，我在这里用的是CART分类回归树。
2、随机森林构造完成之后，给定一组测试数据，使得每个分类器对其结果分类进行评估，最后取评估结果的众数最为最终结果-Random Forest algorithm construction process: 1, by a given raw data, which part of the decision tree data structure, data selected is " back" process, I am here with the CART classification and regression trees. 2, after the completion of the random forest structure, given a set of test data, so that each classifier to uate the results of its classification, the number of all the final results of the assessment to take most of the final results
2、随机森林构造完成之后，给定一组测试数据，使得每个分类器对其结果分类进行评估，最后取评估结果的众数最为最终结果-Random Forest algorithm construction process: 1, by a given raw data, which part of the decision tree data structure, data selected is " back" process, I am here with the CART classification and regression trees. 2, after the completion of the random forest structure, given a set of test data, so that each classifier to uate the results of its classification, the number of all the final results of the assessment to take most of the final results
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下载文件列表
DecisionTree.txt
input.txt
RandomForestTool.txt
TreeNode.txt
CARTTool.txt
Client.txt
input.txt
RandomForestTool.txt
TreeNode.txt
CARTTool.txt
Client.txt
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