Classic machine learning methods
This is an incremental overview for educational purposes, summarizing established methods without new contributions.
The chapter presents classic machine learning methods, focusing on supervised techniques like classification and regression, and briefly covers unsupervised learning for clustering and dimensionality reduction.
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.