Web Document Classification and its Performance Evaluation

摘要

The Web Mining applications have need to be improved with the specific algorithms for the document classification. This paper emphasizes the importance of using appropriate measures and methods for the evaluate of the Web document classification performance. We focus on methods that evaluate how well a classifier performs. The effect of transformations on the confusion matrix are considered for eleven well-known and recently introduced classification measures. We analyze the measure's ability to retain its value under changes in a confusion matrix. We discuss benefits from the use of the invariant and non-invariant measures with respect to characteristics of data classes.