How to Develop a Random Forest Ensemble in Python
by Jason Brownlee on April 20, 2020 in Python Machine Learning
Random forest is an ensemble machine learning algorithm.
It is perhaps the most popular and widely used machine learning algorithm given its good or excellent performance across a wide range of classification and regression predictive modeling problems.
It is also easy to use given that it has few key hyperparameters and sensible heuristics for configuring these hyperparameters.
In this tutorial, you will discover how to develop a random forest ensemble for classification and regression.
After completing this tutorial, you will know:
Random forest ensemble is an ensemble of decision trees and a natural extension of bagging.
How to use the random forest ensemble for classification and regression with scikit-learn.
How to explore the effect of random forest model hyperparameters on model performance.
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