Assessing the performance of classifiers when classes arise from a continuum
- 作者：Mevik ; Bjø ; rn-Helge
- 关键词：Classification ; Classes arising from a continuum ; Measurement error ; Misallocated class labels ; Probability of misclassification ; Squared error rate
- 刊名：Computational Statistics and Data Analysis
- 出版年：2004
- 期刊代码：19_01679473
- 类别：cp
- 出版时间：July 1, 2004
- 卷：46
- 期：4
- 页码：689-705
- 文件大小：270 K
摘要
The situation where classes arise by dividing the range of a continuous response variable into intervals is discussed. The focus is on assessing the performance of classifiers. Due to the underlying continuum, all misclassifications are not equally grave. The probability of misclassification (pmc) is not optimal in this situation. An alternative performance measure, the squared error rate (sqerr) is proposed. It is related to the mean squared error of regression, and penalises misclassifications according to their severity. Also, because of measurement errors in the response variable, there are misallocated class labels in data sets used for training and testing. Estimates of the pmc and the sqerr are developed for this situation. The estimates are tested and compared on a real data set and in a simulation.