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Cost-sensitive feature acquisition and classification

Publication ,  Journal Article
Ji, S; Carin, L
Published in: Pattern Recognition
May 1, 2007

There are many sensing challenges for which one must balance the effectiveness of a given measurement with the associated sensing cost. For example, when performing a diagnosis a doctor must balance the cost and benefit of a given test (measurement), and the decision to stop sensing (stop performing tests) must account for the risk to the patient and doctor (malpractice) for a given diagnosis based on observed data. This motivates a cost-sensitive classification problem in which the features (sensing results) are not given a priori; the algorithm determines which features to acquire next, as well as when to stop sensing and make a classification decision based on previous observations (accounting for the costs of various types of errors, as well as the rewards of being correct). We formally define the cost-sensitive classification problem and solve it via a partially observable Markov decision process (POMDP). While the POMDP constitutes an intuitively appealing formulation, the intrinsic properties of classification tasks resist application of it to this problem. We circumvent the difficulties of the POMDP via a myopic approach, with an adaptive stopping criterion linked to the standard POMDP. The myopic algorithm is computationally feasible, easily handles continuous features, and seamlessly avoids repeated actions. Experiments with several benchmark data sets show that the proposed method yields state-of-the-art performance, and importantly our method uses only a small fraction of the features that are generally used in competitive approaches. © 2006 Pattern Recognition Society.

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Published In

Pattern Recognition

DOI

ISSN

0031-3203

Publication Date

May 1, 2007

Volume

40

Issue

5

Start / End Page

1474 / 1485

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4605 Data management and data science
  • 4603 Computer vision and multimedia computation
  • 0906 Electrical and Electronic Engineering
  • 0806 Information Systems
  • 0801 Artificial Intelligence and Image Processing
 

Citation

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Ji, S., & Carin, L. (2007). Cost-sensitive feature acquisition and classification. Pattern Recognition, 40(5), 1474–1485. https://doi.org/10.1016/j.patcog.2006.11.008
Ji, S., and L. Carin. “Cost-sensitive feature acquisition and classification.” Pattern Recognition 40, no. 5 (May 1, 2007): 1474–85. https://doi.org/10.1016/j.patcog.2006.11.008.
Ji S, Carin L. Cost-sensitive feature acquisition and classification. Pattern Recognition. 2007 May 1;40(5):1474–85.
Ji, S., and L. Carin. “Cost-sensitive feature acquisition and classification.” Pattern Recognition, vol. 40, no. 5, May 2007, pp. 1474–85. Scopus, doi:10.1016/j.patcog.2006.11.008.
Ji S, Carin L. Cost-sensitive feature acquisition and classification. Pattern Recognition. 2007 May 1;40(5):1474–1485.
Journal cover image

Published In

Pattern Recognition

DOI

ISSN

0031-3203

Publication Date

May 1, 2007

Volume

40

Issue

5

Start / End Page

1474 / 1485

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4605 Data management and data science
  • 4603 Computer vision and multimedia computation
  • 0906 Electrical and Electronic Engineering
  • 0806 Information Systems
  • 0801 Artificial Intelligence and Image Processing