How to plot confusion matrix

I have performed my image segmentation using kmeans but need to get the confusion matrix. My image segmentation matrix for six(6) classes has numbers 1 to 6 in it which is perfect. On getting my trained classes BW_1,BW_2,BW_3,BW_4,BW_5,BW_6 I have in each only one's(1's) and zero's(0's) but need to create a single confusion matrix like in this link http://www.mathworks.com/help/nnet/ref/plotconfusion.html?searchHighlight=confusion%2520matrix

Answer 1

[Greg Heath]

The function plotconfusion handles more than 2 classes. Replace the iris_dataset or simplecluster_dataset in the help and doc examples for plotconfusion

    [x,t]        = iris_dataset;
    net          = patternnet;
    rng('default')
    [net tr y e] = train(net,x,t);
    NMSE         = mse(e)/mean(var(t',1)) %0.0418
    R2           = 1-NMSE                 %0.9582
    plotconfusion(t,y);

Find the minimum number of hidden nodes that yields an acceptable result

Hope this helps.

Thank you for formally accepting my answer

Greg

[bayoishola20]

Thank you Greg but just on running line one for class 1.

[x,t]        = BW_class_1;

It tells me "too many arguments".

Please you could look through my comments with star strider above to help me better. The help document doesn't help so much. I anticipate to formally accept your answer. NOTE: I'm a newbie.

[Greg Heath]

That command assumes the input and target matrices are combined as in the MATLAB example database

 help nndatasets
 doc nndatasets

If your data is not formatted that way, then change the command to read the way your data is formatted.

[bayoishola20]

You said the command assumes that my input & target matrices are combined. please in the case where my target matrix are 6 different matrices and each contain only ones and zeros while the input has 1,2,3,4,5,6. How can I achieve this. Thanks in advance.

Answer 2

[Star Strider]

The Neural Network Toolbox confusion function will only let you plot (2x2) classification results. To plot more classes, use the Statistics Toolbox confusion function.

The crosstab function will give you the chi-squared statistic and the probability.

[bayoishola20]

NOTE: I'm just a little familiar with the software.

I just tried using the confusion function and it tells me

Error using confusionmat (line 67)
  G and GHAT need to be vectors or 2D character arrays.

However,

% BW_1 is predicted class 1
% BW_class_1 is known class 1

[C,order] = confusionmat(BW_class_1,BW_1)

where BW_class_1 is <2592x4608 logical>
where BW_1 is <2592x4608 logical>

But as of after segmentation, I had just a matrix called pixel_labels which contained all six(6) classes but I separated it using the code below.

BW_class_1=pixel_labels==1;

Thank you and I anticipate to accept your answer.

[Star Strider]

My pleasure!

I do not completely understand your comment, though. Is your problem solved or do you need more help?

[bayoishola20]

Thank you. My problem is yet to be answered/solved

[Star Strider]

I still do not understand how you could have a matrix of classes. In the confusion matrices I have used in statistics, each element has a known class and a predicted class, in your example, every one being a class numbered 1-6. Your classifier should output a particular class number for each input pattern. Those vectors are then the inputs to your confusion matrix.

[bayoishola20]

I understand that The single matrix from segmentation (kmeans,for six classes) is my input, but I trained six classes (known) using

roipoly function

But this gives me six separate matrices with O's and 1's in them.

I need to,from the single segmentation matrix(predicted) and the six different trained classes(known), compute my confusion matrix.

[Star Strider]

If you have vectors with your known and predicted classes, those are your inputs to your confusion matrix. I got the impression from your Question, specifically ‘My image segmentation matrix for six(6) classes has numbers 1 to 6 in it which is perfect.’ that you already had those and simply wanted to know how to create a confusion matrix for your 6 classes.

[bayoishola20]

Exactly! But am I to combine the trained classes(known, with 0's and 1's) so I could have a single matrix like the predicted or use them as they are? If so, please how do I do that?