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Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
book

Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R

by V Kishore Ayyadevara
June 2018
Intermediate to advanced content levelIntermediate to advanced
379 pages
7h 33m
English
Apress
Content preview from Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
© V Kishore Ayyadevara 2018
V Kishore AyyadevaraPro Machine Learning Algorithms https://doi.org/10.1007/978-1-4842-3564-5_6

6. Gradient Boosting Machine

V Kishore Ayyadevara1 
(1)
Hyderabad, Andhra Pradesh, India
 

So far, we’ve considered decision trees and random forest algorithms. We saw that random forest is a bagging (bootstrap aggregating) algorithm—it combines the output of multiple decision trees to give the prediction. Typically, in a bagging algorithm trees are grown in parallel to get the average prediction across all trees, where each tree is built on a sample of original data.

Gradient boosting , on the other hand, does the predictions using a different format. Instead of parallelizing the tree building process, boosting takes a sequential ...

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ISBN: 9781484235645Purchase LinkPublisher Website