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Keyword

misclassification cost

Description: The loss or penalty associated with assigning an observation to the wrong class, considered in cost-sensitive classification and feature selection.
OpenAlex ID: keywords/misclassification-cost
The foundations of cost-sensitive learning
2001 · Charles Elkan · 1,943
ZETATM analysis A new model to identify bankruptcy risk of corporations
1977 · Edward I. Altman, Robert G. Haldeman, et al. · Journal of Banking & Finance · 1,812
Classification of Imbalanced Data: a Review
2009 · YANMIN SUN, ANDREW K. C. WONG, et al. · International Journal of Pattern Recognition and Artificial Intelligence · 1,699
Neural networks for classification: a survey
2000 · G.P. Zhang · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · 1,673
Transforming classifier scores into accurate multiclass probability estimates
2002 · Bianca Zadrozny, Charles Elkan · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 1,254
Robust Classification for Imprecise Environments
2001 · Foster Provost, Tom Fawcett · Machine Learning · 1,249
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A Bayesian Approach to Filtering Junk E-Mail
1998 · Mehran Sahami, Susan Dumais, et al. · 1,212
Measuring classifier performance: a coherent alternative to the area under the ROC curve
2009 · David J. Hand · Machine Learning · 1,003
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C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling beats Over-Sampling
2003 · Chris Drummond, Robert C. Holte · 786
Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions
1997 · Foster Provost, Tom Fawcett · 724
The superiority of three-way decisions in probabilistic rough set models
2010 · Yiyu Yao · Information Sciences · 683
AdaCost: Misclassification Cost-Sensitive Boosting
1999 · Wei Fan, Salvatore J. Stolfo, et al. · 612
An instance-weighting method to induce cost-sensitive trees
2002 · Kai Ming Ting · IEEE Transactions on Knowledge and Data Engineering · 504
Learning When Data Sets are Imbalanced and When Costs are Unequal and Unknown
2003 · Marcus A. Maloof · 409
Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study
2016 · Deron Liang, Chia-Chi Lu, et al. · European Journal of Operational Research · 399
Financial Statement Fraud Detection: An Analysis of Statistical and Machine Learning Algorithms
2011 · Johan Perols · Auditing A Journal of Practice & Theory · 393
A cost-sensitive decision tree approach for fraud detection
2013 · Yusuf Sahin, Serol Bulkan, et al. · Expert Systems with Applications · 382
Quality assessment of image classification algorithms for land-cover mapping: A review and a proposal for a cost-based approach
1999 · P. C. Smits, S. G. Dellepiane, et al. · International Journal of Remote Sensing · 359
Boosting Trees for Anti-Spam Email Filtering
2001 · Carreras, Xavier, Marquez, Lluis · arXiv (Cornell University) · 357
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Support Vector Machines for Classification in Nonstandard Situations
2002 · Yi Lin, Yoonkyung Lee, et al. · Machine Learning · 348
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Types of Cost in Inductive Concept Learning
2002 · Turney, Peter D. · arXiv (Cornell University) · 340
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Cost curves: An improved method for visualizing classifier performance
2006 · Chris Drummond, Robert C. Holte · Machine Learning · 325
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A Reexamination of Auditor versus Model Accuracy within the Context of the Going‐Concern Opinion Decision*
1994 · WILLIAM HOPWOOD, JAMES C. McKEOWN, et al. · Contemporary Accounting Research · 318
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics
2011 · Victoria López, Alberto Fernández, et al. · Expert Systems with Applications · 317
Layered representations for learning and inferring office activity from multiple sensory channels
2004 · Nuria Oliver, Ashutosh Garg, et al. · Computer Vision and Image Understanding · 316
Works count: 1,600
Citation count: 49,830
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