Authors: Roodschild Matías / [email protected]
Jorge Gotay Sardiñas / [email protected]
Adrián Will / [email protected]
Sebastián Rodriguez / [email protected]
This project was created with mainly academic purposes for my PhD Tesis, but it is also free for commercial uses. Its design goals are: 1) To be accessible to both novices and experts, and 2) To facilitate neural networks manipulations. Froog is free, written 100% in Java, and has been released under Apache 2 license.
Currently Froog supports:
- Backpropagation Algorithm
- Stochastic Gradient Descent
- Conjugate Gradient
- Scaled Conjugate Gradient
- Acceleration methods (Momentum, Momentum Rumelhart, Adam)
- Weight Initialization (Default (Xavier), He, Pitfall, PositiveRandom, SmallRandom)
- Weight Normalization L2
- Dropout
- Loss Functions (RMSE, MSE, CrossEntropy, Logistic)
- Transfer Functions (Logsig, Tansig, Softmax, Purelim, Softplus, ReLU)
- Confusion Matrix
- Early Stop (Max Iteration Only)
//get data
SimpleMatrix input = CSV.open("src/main/resources/iris/iris-in.csv");
SimpleMatrix output = CSV.open("src/main/resources/iris/iris-out.csv");
//Standard Desviation
STD std = new STD();
std.fit(input);
//normalization
input = std.eval(input);
Random random = new Random(1);
//set data in horizontal format (a column is a register and a row is a feature)
input = input.transpose();
output = output.transpose();
//setting backpropagation
Backpropagation bp = new Backpropagation();
bp.setEpoch(1000);
bp.setMomentum(0.9);
bp.setClassification(true);
bp.setLossFunction(LossFunction.CROSSENTROPY);
//number of neurons
int Nhl = 2;
Feedforward net = new Feedforward();
//add layers to neural network
net.addLayer(new Dense(input.numRows(), Nhl, TransferFunction.TANSIG, random));
net.addLayer(new Dense(Nhl, output.numRows(), TransferFunction.SOFTMAX, random));
//train your net
bp.train(net, input, output);
//show results
System.out.println("Print all output");
SimpleMatrix salida = net.output(input);
ConfusionMatrix confusionMatrix = new ConfusionMatrix();
confusionMatrix.eval(Compite.eval(salida.transpose()), output.transpose());
confusionMatrix.printStats();
Froog is in Maven jitpack.io and can easily be added to Maven, and similar project managers.
<repositories>
<repository>
<id>jitpack.io</id>
<url>https://jitpack.io</url>
</repository>
</repositories>
<dependencies>
<dependency>
<groupId>com.github.mroodschild</groupId>
<artifactId>froog</artifactId>
<version>0.5.1</version>
</dependency>
</dependencies>
The main Froog modules depends on the following libraries
- [ EJML 0.41 ] ( http://ejml.org )
- [ Apache Commons-lang3 ] ( https://commons.apache.org/proper/commons-lang/ )
The following is required for unit tests
- [ JUnit ] ( http://junit.sourceforge.net/ )
Froog is released under the Apache 2 open source license.