A Fast Decision Tree Learning Algorithm

There is growing interest in scaling up the widely-used decision-tree learning algorithms to very large data sets. Although numerous diverse techniques have been proposed, a fast tree-growing algorithm without substantial decrease in accuracy and substantial increase in space complexity is essential. In this paper, we present a novel, fast decision-tree learning algorithm that is based on a conditional independence assumption. The new algorithm has a time complexity of O(m

• Type: Conference
• Year: 2006
• Where: AAAI
• Authors: Jiang Su, Harry Zhang
• Keywords: AAAI 2006, Algorithm, Decision-tree Learning Algorithm, Intelligent Agents, Time Complexity