Matlab | divide training set into validation set and test on testing set
I am building a neural network classifier using matlab. For this I have the following dataset.
size(X_Train): 125973 x 122
size(Y_Train): 125973 x 1
size(X_Test): 22543 x 122
size(Y_test): 22543 x 1
As you can see, I already have a testing set I can use. I want to use %20 of my training data set for validation and X_Test and Y_Test for testing. So after constructing my neural network (which I called net) using the network function. I divided the training set using this code:
% divide data into training and test
net.divideParam.trainRatio = 80/100; % 80% training
net.divideParam.valRatio = 20/100; % 20% validation set
I don't want to use net.divideParam.testRatio to divide the training set, but I don't know how to tell the network to use X_Test and Y_Test for testing. Any help?
Edit
I also have an error, it seems that I can't divide the data without using the parameter net.divideFcn(). However, for every value I use in the net.divideFcn(). I get the following error:
Error using network/subsref (line 198)
Index exceeds matrix dimensions.
Error in NN (line 32)
net.divideFcn('dividerand');
Update
For the error I used to have, the solution is so simple. the divideFcn doesn't use () to get parameters:
So this solved the error:
net.divideFcn = 'divideblock'
But I am still trying to find a solution for the first issue.
Bests,
matlab machine-learning neural-network classification supervised-learning
asked Nov 11 at 23:30
U. User
145116
add a comment |
I am building a neural network classifier using matlab. For this I have the following dataset.
size(X_Train): 125973 x 122
size(Y_Train): 125973 x 1
size(X_Test): 22543 x 122
size(Y_test): 22543 x 1
As you can see, I already have a testing set I can use. I want to use %20 of my training data set for validation and X_Test and Y_Test for testing. So after constructing my neural network (which I called net) using the network function. I divided the training set using this code:
% divide data into training and test
net.divideParam.trainRatio = 80/100; % 80% training
net.divideParam.valRatio = 20/100; % 20% validation set
I don't want to use net.divideParam.testRatio to divide the training set, but I don't know how to tell the network to use X_Test and Y_Test for testing. Any help?
Edit
I also have an error, it seems that I can't divide the data without using the parameter net.divideFcn(). However, for every value I use in the net.divideFcn(). I get the following error:
Error using network/subsref (line 198)
Index exceeds matrix dimensions.
Error in NN (line 32)
net.divideFcn('dividerand');
Update
For the error I used to have, the solution is so simple. the divideFcn doesn't use () to get parameters:
So this solved the error:
net.divideFcn = 'divideblock'
But I am still trying to find a solution for the first issue.
Bests,
matlab machine-learning neural-network classification supervised-learning
asked Nov 11 at 23:30
U. User
145116
add a comment |
I am building a neural network classifier using matlab. For this I have the following dataset.
size(X_Train): 125973 x 122
size(Y_Train): 125973 x 1
size(X_Test): 22543 x 122
size(Y_test): 22543 x 1
As you can see, I already have a testing set I can use. I want to use %20 of my training data set for validation and X_Test and Y_Test for testing. So after constructing my neural network (which I called net) using the network function. I divided the training set using this code:
% divide data into training and test
net.divideParam.trainRatio = 80/100; % 80% training
net.divideParam.valRatio = 20/100; % 20% validation set
I don't want to use net.divideParam.testRatio to divide the training set, but I don't know how to tell the network to use X_Test and Y_Test for testing. Any help?
Edit
I also have an error, it seems that I can't divide the data without using the parameter net.divideFcn(). However, for every value I use in the net.divideFcn(). I get the following error:
Error using network/subsref (line 198)
Index exceeds matrix dimensions.
Error in NN (line 32)
net.divideFcn('dividerand');
Update
For the error I used to have, the solution is so simple. the divideFcn doesn't use () to get parameters:
So this solved the error:
net.divideFcn = 'divideblock'
But I am still trying to find a solution for the first issue.
Bests,
matlab machine-learning neural-network classification supervised-learning
asked Nov 11 at 23:30
U. User
145116
I am building a neural network classifier using matlab. For this I have the following dataset.
size(X_Train): 125973 x 122
size(Y_Train): 125973 x 1
size(X_Test): 22543 x 122
size(Y_test): 22543 x 1
As you can see, I already have a testing set I can use. I want to use %20 of my training data set for validation and X_Test and Y_Test for testing. So after constructing my neural network (which I called net) using the network function. I divided the training set using this code:
% divide data into training and test
net.divideParam.trainRatio = 80/100; % 80% training
net.divideParam.valRatio = 20/100; % 20% validation set
I don't want to use net.divideParam.testRatio to divide the training set, but I don't know how to tell the network to use X_Test and Y_Test for testing. Any help?
Edit
I also have an error, it seems that I can't divide the data without using the parameter net.divideFcn(). However, for every value I use in the net.divideFcn(). I get the following error:
Error using network/subsref (line 198)
Index exceeds matrix dimensions.
Error in NN (line 32)
net.divideFcn('dividerand');
Update
For the error I used to have, the solution is so simple. the divideFcn doesn't use () to get parameters:
So this solved the error:
net.divideFcn = 'divideblock'
But I am still trying to find a solution for the first issue.
Bests,
matlab machine-learning neural-network classification supervised-learning
matlab machine-learning neural-network classification supervised-learning
asked Nov 11 at 23:30
U. User
145116
asked Nov 11 at 23:30
U. User
145116
edited Nov 18 at 10:38
asked Nov 11 at 23:30
U. User
145116
asked Nov 11 at 23:30
U. User
145116
asked Nov 11 at 23:30
U. User
145116
145116
add a comment |
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