divideind (Neural Network Toolbox™)

Neural Network Toolbox™

divideind

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Divide vectors into three sets using specified indices

Syntax

[trainV,valV,testV,trainInd,valInd,testInd] = 
divideind(allV,trainInd,valInd,testInd)

Description

divideind is used to separate input and target vectors into three sets: training, validation, and testing. It takes the following inputs,

allV
R x Q matrix of Q R-element vectors

trainInd
Training indices

valInd
Validation indices

testInd
Test indices

`allV`	`R` x `Q` matrix of `Q` `R`-element vectors
`trainInd`	Training indices
`valInd`	Validation indices
`testInd`	Test indices

and returns

trainV
Training vectors

valV
Validation vectors

testV
Test vectors

trainInd
Training indices (unchanged)

valInd
Validation indices (unchanged)

testInd
Test indices (unchanged)

`trainV`	Training vectors
`valV`	Validation vectors
`testV`	Test vectors
`trainInd`	Training indices (unchanged)
`valInd`	Validation indices (unchanged)
`testInd`	Test indices (unchanged)

Examples

p = rands(3,1000);
trainInd = [(1:100) (301:800)];
valInd = [(101:200) (801:900)];
testInd = [(201:300) (901:1000)];
[trainP,valP,testV] = divideind(p,trainInd,valInd,testInd);

Network Use

Here are the network properties that define which data division function to use, and what its parameters are, when train is called.

```
net.divideFcn
net.divideParam
```

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divideblock divideint

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