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Classic machine learning algorithms


In this chapter, we present the main classic machine learning algorithms. A large part of the chapter is devoted to supervised learning algorithms 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. The chapter does not cover neural networks and deep learning.
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Dates and versions

hal-03830094 , version 1 (26-10-2022)
hal-03830094 , version 2 (15-11-2022)
hal-03830094 , version 3 (24-05-2023)
hal-03830094 , version 4 (25-01-2024)




  • HAL Id : hal-03830094 , version 2


Johann Faouzi, Olivier Colliot. Classic machine learning algorithms. Olivier Colliot. Machine Learning for Brain Disorders, Springer, inPress. ⟨hal-03830094v2⟩
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