Confusion matrix neural network

Hello,

The confusion matrix for my NN for classification is below. I'm struggling to understand the numbers. I know the overall correctly classified data is 81.5%.

I would be grateful if somebody had the time to answer a couple of questions.

If I take the 1st row as an example.

What does 22.2% represent?

What does 4 and 14.8% represent?

What does 60.0% (in green) represent?

What does the bottom grey row represent for example 85.7%?

Thanks for your help

Answer 1

[Greg Heath]

Look at column one for class 1 targets

There were 7 class 1 targets

 6 were assigned correctly(GREEN) to output class 1
 1 was assigned incorrectly (RED) to output class 2
 0 were assigned to output class 3 (Ignore colors for 0 entries)
 100*6/7 = 85.7% (GREEN)of class 1 targets were correctly assigned
 100*1/7 = 14.3% (RED) of class 1 targets were incorrectly assigned

Look at row two for targets assigned to class 2

17 targets were assigned to output class 2

1 target from class 1 was incorrectly(RED) assigned to class 2
16 targets from class 2 were correctly(GREEN) assigned to class2
100*16/17 = 94.1%(GREEN) of assignments to class 2 were correct
100*1/17 = 5.9%(RED) of assignments to class 2 were incorrect

Look at interior square percentages

There were 6+1+16+4 = 27 targets

 100*6/27  = 22.2%
 100*1/27  =  3.7%
 100*16/27 = 59.3%
 100*4/27  = 14.8%

If it makes you feel any better, I do not like the format (e.g., I used to use the rows for target classes). However, using the column target format, I use a count confusion matrix and a percent confusion matrix:

 6   0  4  10   
 1  16  0  17 
 7  16  4  27

and

85.7    0  100   37
14.3  100    0   63
100    100  100  100

Hope this helps.

Thank you for formally accepting my answer

Greg

Answer 2

[D C]

Is there any way to display this values in workspace? I got 10 classes and I cannot read them from the diagram because they overlap.

[Vikas]

[c,cm,ind,per] = confusion(targets,outputs)