Random and Deterministic Forests
Forest-based classification and prediction is one of the most commonly used nonparametric statistical methods in many scientific and engineering areas, particularly in machine learning and analysis of high-throughput genomic data. In this chapter, we first introduce the construction of random forests and deterministic forests, and then address a fundamental and practical issue on how large the forests need to be.
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