Prevalence Surveys for Neglected Tropical Diseases

Related lectures (31)

Explores linear models, logistic regression, gradient descent, and multi-class logistic regression with practical applications and examples.

Explores binary response interpretation, link functions, logistic regression, and model selection using deviances and information criteria.

Explores parametric models in data analysis, covering regression estimators, optimization problems, and statistical models.

Covers logistic regression for linear classification and unsupervised dimensionality reduction techniques.

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

Covers linear and logistic regression, including underfitting, overfitting, and performance metrics.

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

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

Explains support vector machine and logistic regression for classification tasks, emphasizing margin maximization and risk minimization.

Explores link prediction, logistic regression, causal inference, and biclustering in statistical network analysis.

Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.

Page 2 of 2