Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Cost-sensitive pruning of decision trees
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Multiple Graph Alignment for the Structural Analysis of Protein Active Sites
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Nearest neighbour group-based classification
Pattern Recognition
ROC curve equivalence using the Kolmogorov-Smirnov test
Pattern Recognition Letters
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In this paper we review the Receiver Operating Characteristic (ROC) curve, and the X^2 test statistic, in relation to the analysis of a confusion matrix. We then show how these two methods are related, and propose an extension to the ROC curve so that it shows contours of X^2 values. These contours can be used to provide further insight into the appropriate setting of the decision threshold for a particular application.