Examples of MauiFilter

• maui.filters.MauiFilter
  This filter converts the incoming data into data appropriate for keyphrase classification. It assumes that the dataset contains three string attributes. The first attribute should contain the name of the file. The second attribute should contain the text of a document from that file. The second attribute should contain the keyphrases associated with that document (if present). The filter converts every instance (i.e. document) into a set of instances, one for each word-based n-gram in the document. The string attribute representing the document is replaced by some numeric features, the estimated probability of each n-gram being a keyphrase, and the rank of this phrase in the document according to the probability. Each new instances also has a class value associated with it. The class is "true" if the n-gram is a true keyphrase, and "false" otherwise. It is also possible to use numeric attributes, if more then one manually selected keyphrase sets per document were available. If the input document doesn't come with author-assigned keyphrases, the class values for that document will be missing. @author Eibe Frank (eibe@cs.waikato.ac.nz), Olena Medelyan(olena@cs.waikato.ac.nz) @version 2.0

Examples of maui.filters.MauiFilter