Chimpanzee Data Analysis

Related lectures (30)

Page 3 of 3

Covers logistic regression, likelihood function, Newton's method, and classification error estimation.

Covers linear models for classification, focusing on logistic regression and support vector machines.

Explores logistic regression for predicting vegetation proportions in the Amazon region through remote sensing data analysis.

Covers the theory and applications of Generalized Linear Models, including MLE, measures of fit, shrinkage, and special examples.

Covers linear and logistic regression for regression and classification tasks, focusing on loss functions and model training.

Explores common probability distributions, special distributions, and entropy concepts.

Explores Generalized Linear Models theory, including logistic and Poisson regression, model evaluation, and coefficient tests.

Covers linear models for multi-class classification, focusing on logistic regression and evaluation metrics.

Introduces linear regression, generalized linear models, and mixed-effect models for regression analysis.

Covers the theory behind Maximum Likelihood Estimation, discussing properties and applications in binary choice and ordered multiresponse models.