【文件属性】:
文件名称:Machine Learning With Random Forests And Decision Trees - A Visual Guide
文件大小:1.53MB
文件格式:MOBI
更新时间:2020-11-08 06:50:26
Machine Learning
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 to 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
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- 这本书很不错的