lda

Splitting the data into training and testing sets is a common step in evaluating the performance of a learning algorithm. It’s more clear-cut for supervised learning, wherein you train the model on the training set, then see how well its classifications on the test set match the true class labels. For unsupervised learning, such evaluation … Read more