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In this chapter, we will look at random forests – a versatile, non-linear model that can be used for both regression and classification. Random forests have an impressive mathematical and statistical pedigree to be labeled as advanced statistical models, and their use of decision trees as weak learners and their reliance on bagging of data for training an ensemble of decision trees makes them among the more widely adopted machine learning tools.

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Random Forest

  • 章节

  • 发表日期：

    2025年

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  • Samit Ahlawat

摘要

In this chapter, we will look at random forests – a versatile, non-linear model that can be used for both regression and classification. Random forests have an impressive mathematical and statistical pedigree to be labeled as advanced statistical models, and their use of decision trees as weak learners and their reliance on bagging of data for training an ensemble of decision trees makes them among the more widely adopted machine learning tools.