Classic machine learning methods
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Abstract (arXiv)
In this chapter, we present the main classic machine learning methods. A large part of the chapter is devoted to supervised learning techniques for classification and regression, including nearest-neighbor methods, linear and logistic regressions, support vector machines and tree-based algorithms. We also describe the problem of overfitting as well as strategies to overcome it. We finally provide a brief overview of unsupervised learning methods, namely for clustering and dimensionality reduction.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 0 of its 29 references that are in the map. First posted on arXiv 24 May 2023.
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