| Project/Area Number |
23500284
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Osaka University of Economics and Law (2013)
Osaka Prefecture University (2011-2012) |
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Principal Investigator |
|
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| Co-Investigator(Kenkyū-buntansha) |
HONDA Katsuhiro 大阪府立大学, 大学院・工学研究科, 教授 (80332964)
NOTSU Akira 大阪府立大学, 大学院・工学研究科, 准教授 (40405345)
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2013: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2012: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2011: ¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
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| Keywords | 識別器 / クラスター分析 / 画像処理 / クラスタリング / 自動監視 / 協調フィルタリング / 強化学習 / ファジィクラスタリング / ２分木 / 主成分分析 / 2分木 |
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| Research Abstract |
Fuzzy c-Means based Classifier (FCMC) is a simple approach to classification based on the clustering and parameter optimization methods. The training time and testing time of FCMC are significantly improved. FCMC and the state of the art classifier: LibSVM are compared. The two parameters are automatically optimized by the revised random search approach. When the number of training samples is more than a million, the total training time for FCMC is estimated to be two to three orders of magnitude smaller than LibSVM, while FCMC achieves the same level of classification accuracy with LibSVM.
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