Minitab Cart Jun 2026

Your data is complete, no missing values, and predictors are measured reliably (e.g., continuous measurements from a stable process).

CART (Classification and Regression Trees) is a type of decision tree analysis that uses a tree-like model to classify data or predict continuous outcomes. The technique was first introduced by Leo Breiman and colleagues in the 1980s. CART is a non-parametric method, meaning it doesn't require any specific distribution of the data. The algorithm works by recursively partitioning the data into smaller subsets based on the values of the predictor variables. minitab cart

The algorithm looks at all possible ways to split the data into two parts (binary splits). It selects the split that creates the most significant difference in the response variable. Your data is complete, no missing values, and

from tree: If Pour temp > 1380°C → No defect (98% correct) CART is a non-parametric method, meaning it doesn't