Description: Random forests are used in a random way to build a forest, there are a lot of decision trees in the forest, there is no association between the random forest of each decision tree. In the forest, when there is a new input into the sample, let every decision tree in the forest was a judge, look at the sample which should belongs to a class, and then take a look at what kind of choice is the most, the predicted samples for that class.
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File list (Check if you may need any files):
random-forest\computer_score.Rmd
.............\lr_real_buy.R
.............\rf1.Rmd
.............\rf_demo.html
.............\rf_demo.md
.............\rf_demo.Rmd
.............\rf_user_brand_analysis.Rmd
random-forest
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