Module regressor 

First-order regression tree learners.

This module is the regression analogue of classifier, but the split logic differs in one important way: regression quality depends on leaf value statistics rather than class counts. The implementation therefore leans on cached count/sum/sum-of-squares histograms in the mean-criterion hot path.

Structs

DecisionTreeRegressor

Concrete trained regression tree.

RegressionTreeOptions

Shared training controls for regression tree learners.

Enums

RegressionTreeAlgorithm

RegressionTreeError

Functions

train_cart_regressor

train_cart_regressor_with_criterion

train_oblivious_regressor

train_oblivious_regressor_with_criterion

train_randomized_regressor

train_randomized_regressor_with_criterion