A Streaming Parallel Decision Tree Algorithm

A new algorithm for building decision tree classifiers is proposed. The algorithm is executed in a distributed environment and is especially designed for classifying large datasets and streaming data. It is empirically shown to be as accurate as standard decision tree classifiers, while being scalable to infinite streaming data and multiple processors.

• Type: Journal
• Year: 2010
• Where: JMLR
• Authors: Yael Ben-Haim, Elad Tom-Tov
• Keywords: Decision Tree Classifiers, Distributed Environment, JMLR 2010, Standard Decision Tree