古川 直広 （九州大学大学院システム情報科学研究科 情報理学専攻・発見科学講座）
I developed a machine learning system HAKKE which is suitable for predicting functional regions from sequences, such as protein-coding region prediction, and transmembrane domain prediction. HAKKE is a hybrid system cooperated by a number of algorithms of a pool to make an accurate prediction. The system uses an extension of the weighted majority algorithm in order to fit the strength of each algorithm into given training examples. In this seminar, we describe the core of the system and show some experimental results on transmembrane domain and alpha-helix predictions.