A.By minimizing the number of leaf nodes

B.By maximizing information gain or Gini impurity reduction

C.Based on the order of appearance in the dataset

D.Randomly assigned

A.To identify outliers in the data

B.To capture the relationship between predictors and the response variable

C.To assess multicollinearity among predictors

D.To calculate the p-values of the predictors

A.Statistics for each cluster, such as mean and standard deviation

B.The number of variables in the analysis

C.The decision tree structure for each cluster

D.The number of iterations performed during clustering

A.The p-value of the intercept term

B.The R-squared value

C.The learning rate of the model

D.The AUC (Area Under the Curve)

A.At least two variables are required.

B.A target variable is required.

C.Interaction items are allowed.

D.Category items are not allowed.