An Algorithm for Generating Individualized Treatment Decision Trees and Random Forests

Privately Evaluating Decision Trees and Random Forests

Decision trees and random forests are common classifiers with widespread use. In this paper,we develop two protocols for privately evaluating decision trees and random forests. We operatein the standard two-party setting where the server holds a model (either a tree or a forest),and the client holds an input (a feature vector). At the conclusion of the protocol, the clientlearns...

Embedding Decision Trees and Random Forests in Constraint Programming

In past papers, we have introduced Empirical Model Learning (EML) as a method to enable Combinatorial Optimization on real world systems that are impervious to classical modeling approaches. The core idea in EML consists in embedding a Machine Learning model in a traditional combinatorial model. So far, the method has been demonstrated by using Neural Networks and Constraint Programming (CP). I...

An Algorithm for Generating Abstract Syntax Trees

syntax 61 Computer Programming and Software

A Note On Rémy's Algorithm For Generating Random Binary Trees

Forests of Decision Trees

In many cases it is better to extract a set of decision trees and a set of possible logical data descriptions instead of a single model. Methods for creating forests of decision trees based on Separability of Split Value (SSV) criterion are presented. Preliminary results confirm their usefulness in understanding data structures.