Probabilistic Intervals of Confidence

نویسنده

  • Norbert Jankowski
چکیده

Abstract: High accuracy should not be the only goal of classification: information concerning probable alternatives diagnoses, probability of these diagnoses, evaluation of confidence in classification, are also important. Neural models are used just to obtain the winner class but do not provide any justification for their recommendations – they work as black boxes. A method which determine confidence intervals and probabilistic confidence intervals is presented here. It helps to evaluate the certainty of the winning class and the importance of alternative classes. Probabilistic intervals are also useful to compare the influence of each feature in classification of a given case, showing changes of the probability of all important classes. Probabilistic confidence intervals help to visualize the class memberships of a given case and its neighborhood.

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تاریخ انتشار 2000