did i need target matrix for new input testing??
1 次查看(过去 30 天)
显示 更早的评论
hi...i create neural network....the input matrix is with 18X20...(18= number of features and 20 = number of images for 2 classes)the target matrix is 2X20...after traning i want test the network with new image...the new enter images is matrix of 18X1.. i used this method for testing it:
simpleclassOutputs = sim(mynet11,input); figure();plotroc(T,simpleclassOutputs);
T= is target matrix which used in traning>> the error is ... Index exceeds matrix dimensions.
note: i used R2013a matlab and i am new in neural network
Error in plotconfusion>update_plot (line 396) y = y(:,known);
Error in plotconfusion (line 108) plotData = update_plot(param,fig,plotData,update_args{:});
Error in train (line 223) figure,plotconfusion(T,out);
my question is: how to sove this problem?? did i need target matrix for new input testing?? plz help me/
0 个评论
采纳的回答
Greg Heath
2014-6-13
If you have a new input you can use the net to obtain an output and the corresponding classification. However, without the corresponding target, you cannot determine, directly, if the classification is correct. Of course you could use the original data and design multiple classifiers of different types to estimate the probability of the classification being correct.
I think the roc plot needs output and target to be of the same size.
Hope this helps.
Thank you for formally accepting my answer
Greg
1 个评论
Image Analyst
2014-6-15
primrose's 3 "Answers" moved here since they were not actually answers to the original posted question but actually replies to Greg.
thanks greg for your replay...i dont understand your answer can you explane your answer,,can i solve my problem or not>> ??? plz help me
plz can you help me??? after trainig network how can display the images matching which has high simlirty with testing images????????
hi greg ...this is my file ..can you help me plz
By the way, no file was attached in the "Answer".
更多回答(3 个)
primrose khaleed
2014-6-15
2 个评论
Greg Heath
2014-6-16
class = vec2ind(output) will give a 1 or 2 for each column of output.
If you know the correct class you can count the errors for each class and obtain the class per cent error rates.
Since each class is defined by multiple examples, how do you want to display the correct answer as a single image? The mean of the class members or the member that is the most similar?
Your choice.
primrose khaleed
2014-6-17
2 个评论
Greg Heath
2014-6-18
No, it is not correct. You used the ANSWER block instead of the COMMENT BLOCK.
plotconfusion is for matrices (not vectors) of the same size. Use confusion otherwise.
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!