Acquisition of Multiple Tree Structured Patterns by an Evolutionary Method Using Sets of Tag Tree Patterns as Individuals
Shotarou Tani, Tetsuhiro Miyahara, Yusuke Suzuki, Tomoyuki Uchida · 2015
Knowledge acquisition from tree structured data is an important task in machine learning and data mining. A tag tree pattern is a rooted tree structured pattern which has ordered children and structured variables representing arbitrary sub tree structures. In order to represent tree structured data about complex phenomena, we propose a learning method for acquiring characteristic multiple tree structured patterns by evolutionary computation using sets of tag tree patterns as individuals, from positive and negative tree structured data.