Which of the following can be used to create sub–samples using a maximum dissimilarity approach?

A. Linear Regression B. K-Means Clustering C. Decision Tree D. Logistic Regression

A. The model performs well on the test data B. The model fits the training data perfectly C. The model fails to generalize D. The model is too simple to learn patterns

A. Support Vector Machine (SVM) B. K-Means Clustering C. Random Forest D. Linear Regression

A. To minimize errors on the training data B. To create a linear regression model C. To visualize data relationships D. To classify data points into categories