New feature selection and weighting methods based on category information

The traditional methods of feature selection and weighting make the best of document information, but despise or ignore the category information. The new feature selection and weighting methods use category information as a factor, which make up the disadvantages of traditional methods. Using new methods, the features distributed equally on a single category are more important than using old methods. It is proved by the experiment that four famous classifiers based on new feature selection and weighting methods are more effective than those based on traditional methods.