Classic Machine Learning Methods
Johann Faouzi, Olivier Colliot
Abstract
Abstract 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. The chapter does not cover neural networks and deep learning as these will be presented in Chaps. 3 , 4 , 5 , and 6 .
Topics & Concepts
OverfittingArtificial intelligenceMachine learningComputer scienceDimensionality reductionCluster analysisUnsupervised learningSupport vector machineArtificial neural networkSupervised learningPattern recognition (psychology)Time Series Analysis and ForecastingAnomaly Detection Techniques and ApplicationsNeural Networks and Applications