October 2018
Intermediate to advanced
172 pages
4h 6m
English
Content preview from Machine Learning with scikit-learn Quick Start Guide
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Summary
While this chapter was rather long, you have entered the world of tree based algorithms, and left with a wide arsenal of tools that you can implement in order to solve both small- and large-scale problems. To summarize, you have learned the following:
- How to use decision trees for classification and regression
- How to use random forests for classification and regression
- How to use AdaBoost for classification
- How to use gradient boosted trees for regression
- How the voting classifier can be used to build a single model out of different models
In the upcoming chapter, you will learn how you can work with data that does not have a target variable or labels, and how to perform unsupervised machine learning in order to solve such problems! ...
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