AdaBoost with different costs for misclassification and its applications to contextual image classification

Ryuei Nishii, Shuji Kawaguchi

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

抄録

Consider a confusion matrix obtained by a classifier of land-cover categories. Usually, misclassification rates are not uniformly distributed in off-diagonal elements of the matrix. Some categories are easily classified from the others, and some are not. The loss function used by AdaBoost ignores the difference. If we derive a classifier which is efficient to classify categories close to the remaining categories, the overall accuracy may be improved. In this paper, the exponential loss function with different costs for misclassification is proposed in multiclass problems. Costs due to misclassification should be pre-assigned. Then, we obtain an emprical cost risk function to be minimized, and the minimizing procedure is established (Cost AdaBoost). Similar treatments for logit loss functions are discussed. Also, Spatial Cost AdaBoost is proposed. Out purpose is originally to minimize the expected cost. If we can define costs appropriately, the costs are useful for reducing error rates. A simple numerical example shows that the proposed method is useful for reducing error rates.

本文言語英語
ホスト出版物のタイトルImage and Signal Processing for Remote Sensing XII
DOI
出版ステータス出版済み - 2006
イベントImage and Signal Processing for Remote Sensing XII - Stockholm, スウェーデン
継続期間: 9月 11 20069月 14 2006

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
6365
ISSN(印刷版)0277-786X

その他

その他Image and Signal Processing for Remote Sensing XII
国/地域スウェーデン
CityStockholm
Period9/11/069/14/06

!!!All Science Journal Classification (ASJC) codes

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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