Combined classifier design based on random forest-
2016-08-23
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Random forests as its name implies, is in a random manner to build a forest, the forest is made up of many decision trees, random forests each decision tree is separated. After getting the forest when there is a new input sample when entering, let each decision tree in the forest, respectively, for judgment, check out this sample belongs to which category (classification), and see which one was selected most, predicted the sample for that category.
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