[4G2-OS-8a] マイニングと知識創発(1)

[4G2-OS-8a-04] Extraction of Classification Patterns from Deep Learning Networks

〇MASAYUKI ANDO¹, Yoshinobu Kawahara^3,4, Wataru Sunayama², Yuji Hatanaka² (1. Graduate School of Engineering, The University of Shiga Prefecture, 2. School of Engineering, The University of Shiga Prefecture, 3. Institute of Mathematics for Industry, Kyushu University, 4. RIKEN Center for Advanced Intelligence Project)

Keywords:Deep Learning, Text Mining, Interpretation Support

In deep learning, there is a problem that concrete classification patterns for deriving reasons for classification are often incomprehensible. In this paper, we propose a classification patterns extraction system from deep learning networks and verified the effectiveness of the system. The proposed system takes out learning networks from the learning result of deep learning and extracts classification patterns from the learning networks. Then the system displays the extracted classification patterns so that users of the system can interpret the learning networks. In verification experiments, the significance of the extracted classification patterns was estimated by chi-square test. The results showed that users of the system can extract classification patterns effective for interpretations of the learning networks by using the proposed system.