Speaker
Anna Scaife
(University of Manchester)
Description
This lecture introduces machine learning for classification in a general way before demonstrating a specific example of classification using random forests. The lecture describes the concepts of training, validation and test data sets, and introduces the problem of class imbalance and various methods for addressing this issue. The lecture gives an overview of standard performance metrics, including those for specific machine learning classification problems, and introduces the receiver operating characteristic (ROC) curve.
