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!!

 채택된 답변

Greg Heath
Greg Heath 2013년 12월 13일
편집: Greg Heath 2013년 12월 14일

1 개 추천

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

댓글 수: 2

Michael Dorner
Michael Dorner 2013년 12월 14일
편집: Michael Dorner 2013년 12월 14일
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 2013년 12월 15일
Show your code, dimensions of input and target, comments and error messages

댓글을 달려면 로그인하십시오.

추가 답변 (0개)

카테고리

도움말 센터 및 File Exchange에서 Deep Learning Toolbox에 대해 자세히 알아보기

질문:

2013년 12월 13일

댓글:

2013년 12월 15일

Community Treasure Hunt

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

Start Hunting!

Translated by