TS: a test-split algorithm for inductive learning
Xindong Wu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
This paper presents a new attribute-based learning algorithm, TS. Different from ID3, AQ11, and HCV in strategies, this algorithm operates in cycles of test and split. It uses those attribute values which occur only in positives but not in negatives to straightforwardly discriminate positives against negatives and chooses the attributes with least number of different values to split example sets. TS is natural, easy to implement, and low-order polynomial in time complexity.