The MDF discrimination measure: Fisher in disguise
نویسندگان
چکیده
Recently, a discrimination measure for feature extraction for two-class data, called the maximum discriminating (MDF) measure (Talukder and Casasent [Neural Networks 14 (2001) 1201-1218]), was introduced. In the present paper, it is shown that the MDF discrimination measure produces exactly the same results as the classical Fisher criterion, on the condition that the two prior probabilities are chosen to be equal. The effect of unequal priors on the efficiency of the measures is also discussed.
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ورودعنوان ژورنال:
- Neural networks : the official journal of the International Neural Network Society
دوره 17 4 شماره
صفحات -
تاریخ انتشار 2004