Misclassification cost in neural networks

3 次查看(过去 30 天)
I was wondeing if it is possible to put weights on false positive and false negatives, the same as the misclassification cost array in random forest and SVM?
Explaining what I mean by misclassification cost: Misclassification cost, specified as a numeric square matrix, where Cost(i,j) is the cost of classifying a point into class j if its true class is i. For two-class learning, if you specify the cost matrix ? (see Cost), then the software updates the class prior probabilities p (see Prior) to pc by incorporating the penalties described in ?. (at https://au.mathworks.com/help/stats/classificationsvm.html)
Defining C in a matrix like this (C=[0 alpha beta 0]) you will be able to put weights on FP and FN by varying beta and alpha. Is this also possible in neural nets?
  1 个评论
M J
M J 2021-2-16
Hi, did you figure it out? I'm currently facing the same problem. Thanks!

请先登录,再进行评论。

回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Pattern Recognition and Classification 的更多信息

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by