Khaksar asked . 2021-08-03

How can i put the conditional statement

How can i put the conditional statement ( If-Then-else) on the specific elements (Rows/columns) of a matrix in Matlab Using Neural Network Tool? Basically I am working on classification using neural Network tool in matlab. My out put only shows in matrix like : output =

    1.2723
    0.0123
    0.0022
But I want the output in statement like "Class1" Or "Class2"
i.e. If the matrix is like this then output is this....

For example: I have two different matrices like: output1 =

    1.2723
    0.0123
    0.0022

output2 =

    0.2460
   -0.0521
    1.1062

%I want to set the ranges of the elements on behalf of some conditions like:

 If The first element of the  first row of matrix Output1 is >= 0.6 and <=1.5

AND

If The 2nd element of the 2nd row of matrix Output1 is >= -0.49 and <=0.49

AND

If The 3rd element of the 3rd row of matrix Output1 is >= -0.49 and <=0.49

THEN

Display = Class1

%for Matrix Output2:

I want to set the ranges of the elements on behalf of some conditions like:

If The 1st element of the 1st row of matrix Output2 is >= -0.49 and <=0.49

AND

If The 2nd element of the 2nd row of matrix Output2 is >= -0.49 and <=0.49

AND

If The 3rd element of the 3rd row of matrix Output2 is >= 0.6 and <=1.5

THEN

Display = Class2

Please anyone can send me the code/explanation. how can I set these condition using If-Then-else or any other statement?

neural network , matrix element ext... , if-then-else condi...conditions of row ... matrix manipulat

Expert Answer

Prashant Kumar answered . 2024-12-21 01:02:13

If you have 4 classes, your target matrix columns should be columns of eye(4). The relationship between class indices 1:4 and the target matrix is

 trueclassindices = vec2ind(target)
 target           = ind2vec(trueclassindices)

Example:

 >> trueclassindices = [ 1 1 2 4 3 4  ]
 >> target           = full( ind2vec(trueclassindices))

 target =   1     1     0     0     0     0     
            0     0     1     0     0     0  
            0     0     0     0     1     0 
            0     0     0     1     0     1

 output =[ 0.5142 0.49114  0.18198      0     0.25288    0.13838
          0.03653 0.1455   0.4168   0.14434   0.18459    0.066341
          0.31642 0.22294  0.26658  0.38809   0.54807    0.35987
          0.13285 0.14041  0.13464  0.46757   0.014469   0.43541]

then

 assignedclasses =   1     1     2     4     3     4

PS. The unit sum output is a consistent estimate of the input-conditional posterior class probabilities

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