Hej, I have a problem. Using the NN toolbox a neural network shall be trained to recognize a two class problem. I used the default settings ( dividerand , 10 hidden neurons, divide radio 0.7, 0.15, 0.15) and my input is a 3xn matrix and my target is a 2xn matrix ([0; 1] for class one and [1; 0] for class two for each sample), where n=21000. the ratio of the classes are about 3:2.
Why my confusion matrix looks like:
Thank you very much!!

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Greg Heath
Greg Heath 2013 年 12 月 13 日
編集済み: Greg Heath 2013 年 12 月 14 日

1 投票

Class 1 target should be [1;0] and class 2 should be [0;1]
N1 = 13840, N1trn = 9421, N1val = 2044, N1tst = 2015
N2 = 7895, N2trn = 5542, N2val = 1162, N2tst = 1191
All inputs except one class2 validation vector are classified as class 1
The confusion matrix format could be revised to make it easier to understand.
Thank you for formally accepting my answer.
Greg

2 件のコメント

Michael Dorner
Michael Dorner 2013 年 12 月 14 日
編集済み: Michael Dorner 2013 年 12 月 14 日
Thank you for answering. Unfortunately, I tried it with 50:50 data, but still the same result. The second (and further classes) are almost not detected, but they should, at least as wrong. In the sample code (e.g. iris_data) they are ok, even for two classes (although in this case the hitrate is quite bad :-) ).
Greg Heath
Greg Heath 2013 年 12 月 15 日
Show your code, dimensions of input and target, comments and error messages

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