Which of the following can also be used to find new variables that are linear combinations of the original set with independent components?

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