Partial least squares regression

Related lectures (28)

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Covers the MSE problem in linear regression models, focusing on the optimal estimator and data fusion methods.

Explores the extension of linear classifiers to handle multiclass problems and compares their performance on various datasets.

Covers visualizations in orthonormal bases in R2, focusing on rotations and reflections.

Covers linear regression basics, closed-form solutions, singularity, and regularizing techniques.

Covers linear and weighted regression, limitations, and introduces locally weighted regression for model-free regression.

Explores linear models for classification, including logistic regression, decision boundaries, and support vector machines.

Explores linear models for classification, logistic regression, decision boundaries, SVM, multi-class classification, and practical applications.

Covers linear models, binary and multi-class classification, and logistic regression with practical examples.