Labeled data for classification could often be obtained by sampling that restricts or favors choice of certain classes. A classifier trained using such data will be biased, resulti...
When building an application that requires object class recognition, having enough data to learn from is critical for good performance, and can easily determine the success or fai...
We apply decision tree induction to the problem of discourse clue word sense disambiguation. The automatic partitioning of the training set which is intrinsic to decision tree ind...
A method for inductivelearningof primitive features is proposed. Primitive features are well investigated and they are extracted in bottom-up manner fiom training set of patterns ...
The present article demonstrates a way of formulating a neuro-fuzzy approach for feature extraction under unsupervised training. A fuzzy feature evaluation index for a set of feat...