Data Complexity Analysis for Classifier Combination
نویسنده
چکیده
Multiple classiier methods are eeective solutions to diicult pattern recognition problems. However, empirical successes and failures have not been completely explained. Amid the excitement and confusion , uncertainty persists in the optimality of method choices for speciic problems due to strong data dependences of classiier performance. In response to this, I propose that further exploration of the methodology be guided by detailed descriptions of geometrical characteristics of data and classiier models.
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