Classic machine learning methods

Johann Faouzi, Olivier Colliot
5/24/2023
cs.LGcs.AI

No confident code implementation found for this paper. 4 possible matches can be shown below.

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 4 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{faouzi2023classic,
  title  = {Classic machine learning methods},
  author = {Johann Faouzi and Olivier Colliot},
  year   = {2023},
  eprint = {2310.11470},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.11470v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2310.11470.svg)](https://codeofpaper.com/paper/2310.11470)

Discussion