...he observations by univariate splits in a recursive way Step 2: fit a constant model in each cell of the resulting partition. Most prominent representatives: ‘CART’ (Breiman et al., 1984) and ‘C4.5’ (=-=Quinlan, 1993-=-), both implementing an exhaustive search. Two Fundamental Problems Overfitting: Mingers (1987) notes that the algorithm [. . . ] has no concept of statistical significance, and so cannot distinguish ...

...age algorithm: Step 1: partition the observations by univariate splits in a recursive way Step 2: fit a constant model in each cell of the resulting partition. Most prominent representatives: ‘CART’ (=-=Breiman et al., 1984-=-) and ‘C4.5’ (Quinlan, 1993), both implementing an exhaustive search. Two Fundamental Problems Overfitting: Mingers (1987) notes that the algorithm [. . . ] has no concept of statistical significance,...

....978) * 0.955 (0.940, 0.970) * 0.495 (0.471, 0.519)s1.050 (1.041, 1.058) * 1.086 (1.076, 1.096) * Summary The separation of variable selection and split point estimation first implemented in ‘CHAID’ (=-=Kass, 1980-=-) is the basis for unbiased recursive partitioning for responses and covariates measured at arbitrary scales. The statistical internal stop criterion ensures that interpretations drawn from such trees...