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Filtering by: Creator Margineantu, Dragos D. (Dragos Dorin)

Learning decision trees for loss minimization in multi-class problems

Creator:

Oregon State University. Dept. of Computer Science, Margineantu, Dragos D. (Dragos Dorin), and Dietterich, Thomas G.

Abstract:

Many machine learning applications require classifiers that minimize an asymmetric loss function rather than the raw misclassification rate. We study methods for modifying C4.5 to incorporate arbitrary loss matrices. One way to incorporate loss information into C4.5 is to manipulate the weights assigned to the examples from different classes. For...

Resource Type:

Research Paper
Bootstrap methods for the cost-sensitive evaluation of classifiers

Creator:

Oregon State University. Dept. of Computer Science, Margineantu, Dragos D. (Dragos Dorin), and Dietterich, Thomas Glen

Abstract:

Many machine learning applications require classifiers that minimize an asymmetric cost function rather than the misclassification rate, and several recent papers have addressed this problem. However, these papers have either applied no statistical testing or have applied statistical methods that are not appropriate for the cost-sensitive setting. Without good statistical...

Resource Type:

Research Paper