Overview of Classification
Автор: Carlos Fernandez-Granda
Загружено: 2025-06-27
Просмотров: 68
We provide an overview of classification, where we cover the two main strategies for building classifiers: generative and discriminative. Generative models include Naive Bayes and Gaussian discriminant analysis. Discriminative models can be linear (e.g. logistic and softmax regression) or nonlinear (e.g. neural networks or tree-based models). In addition, we discuss how to evaluate the performance, discriminative ability and calibration of a classifier.
Probability and statistics book: https://a.co/d/7k259eb
Website with free preprint, videos, slides and solutions to exercises: https://www.ps4ds.net
Slides for this video: https://github.com/cfgranda/ps4ds/blo...
Other videos on classification: https://www.ps4ds.net/videos/regressi...
Naive Bayes: • Why Probabilistic Modeling is Hard: The Cu...
Gaussian discriminant analysis: • Gaussian Discriminant Analysis for Alzheim...
Code: https://www.ps4ds.net/code/regression...
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