How can I do a 50-50 split on data to obtain train and test datasets such that no value is common to both sets?
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I am new to matlab and I can't find a function to do this.
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Walter Roberson
2016-9-11
"The divide function is accessed automatically whenever the network is trained, and is used to divide the data into training, validation and testing subsets. If net.divideFcn is set to 'dividerand' (the default), then the data is randomly divided into the three subsets using the division parameters net.divideParam.trainRatio, net.divideParam.valRatio, and net.divideParam.testRatio. The fraction of data that is placed in the training set is trainRatio/(trainRatio+valRatio+testRatio), with a similar formula for the other two sets. The default ratios for training, testing and validation are 0.7, 0.15 and 0.15, respectively."
net.divideParam.trainRatio = 0.5;
net.divideParam.testRatio = 0.5;
net.divideParam.valRatio = 0;
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Greg Heath
2016-9-11
Since you are new at this my advice is to begin using all of the defaults. Short examples are given in the documentation. See
REGRESSION/CURVEFITTING
help fitnet
doc fitnet
CLASSIFICATION/PATTERNRECOGNITION
help patternnet
doc patternet
For zillions of examples search in both the NEWSGROUP and ANSWERS using the search words
greg fitnet
greg patternnet
Hope this helps.
Greg
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