Decision tree regression is a fundamental machine learning technique to predict a single numeric value. A decision tree regression system incorporates a set of virtual if-then rules to make a ...

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...

There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...

Linear Trees combine the learning ability of Decision Tree with the predictive and explicative power of Linear Models. Like in tree-based algorithms, the data are split according to simple decision ...

Abstract: Traditional decision trees also known as vanilla decision trees, use axis-aligned splits and are interpretable. Alternate implementations known as linear decision trees use oblique splits to ...

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Abstract: Objectives: This paper proposes a novel stability metric for decision trees that does not rely on the elusive notion of tree similarity. Existing stability metrics have been constructed in a ...

# Use the skeleton below for the classifier and insert your code here. feature_index : int, optional, Index of the feature this node splits on. Default is None. threshold : float, optional, Threshold ...