文件名称:
Machine Learning With Random Forests And Decision Trees - A Visual Guide
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文件大小: 1mb
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上传时间: 2017-10-19
详细说明： Topics Covered The topics covered in this book are An overview of decision trees and random forests A manual example of how a human would classify a dataset, compared to how a decision tree would work How a decision tree works, and why it is prone t o overfitting How decision trees get combined to form a random forest How to use that random forest to classify data and make predictions How to determine how many trees to use in a random forest Just where does the "randomness" come from Out of Bag Errors & Cross Validation - how good of a fit did the machine learning algorithm make? Gini Criteria & Entropy Criteria - how to tell which split on a decision tree is best among many possible choices And More ...展开收缩
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