Using Neural Network Class in WEKA in Java code
java, weka
Solution
Following steps might be able to help you:
- Add Weka libraries
Download Weka from http://www.cs.waikato.ac.nz/ml/weka/downloading.html.
From the package find 'Weka.jar' and add in the project.
Java Code Snippet
Building a Neural Classifier
public void simpleWekaTrain(String filepath)
{
try{
//Reading training arff or csv file
FileReader trainreader = new FileReader(filepath);
Instances train = new Instances(trainreader);
train.setClassIndex(train.numAttributes() – 1);
//Instance of NN
MultilayerPerceptron mlp = new MultilayerPerceptron();
//Setting Parameters
mlp.setLearningRate(0.1);
mlp.setMomentum(0.2);
mlp.setTrainingTime(2000);
mlp.setHiddenLayers(“3?);
mlp.buildClassifier(train);
}
catch(Exception ex){
ex.printStackTrace();
}
}
Another Way to set parameters,
mlp.setOptions(Utils.splitOptions(“-L 0.1 -M 0.2 -N 2000 -V 0 -S 0 -E 20 -H 3?));
Where,
L = Learning Rate
M = Momentum
N = Training Time or Epochs
H = Hidden Layers
etc.
- Neural Classifier Training Validation
For evaluation of training data,
Evaluation eval = new Evaluation(train);
eval.evaluateModel(mlp, train);
System.out.println(eval.errorRate()); //Printing Training Mean root squared Error
System.out.println(eval.toSummaryString()); //Summary of Training
To apply K-Fold validation
eval.crossValidateModel(mlp, train, kfolds, new Random(1));
Evaluating/Predicting unlabelled data
Instances datapredict = new Instances(
new BufferedReader(
new FileReader(<Predictdatapath>)));
datapredict.setClassIndex(datapredict.numAttributes() – 1);
Instances predicteddata = new Instances(datapredict);
//Predict Part
for (int i = 0; i < datapredict.numInstances(); i++) {
double clsLabel = mlp.classifyInstance(datapredict.instance(i));
predicteddata.instance(i).setClassValue(clsLabel);
}
//Storing again in arff
BufferedWriter writer = new BufferedWriter(
new FileWriter(<Output File Path>));
writer.write(predicteddata.toString());
writer.newLine();
writer.flush();
writer.close();
Problem
Hi I want to do simple training and testing using Neural Network in WEKA library. But, I find it is not trivial, and its different with NaiveBayes class in its library. Anyone have example how to use this class in java code?