Froog Authors: Roodschild Matias / mroodschild@gmail.com Jorge Gotay Sardinas / jgotay57@gmail.com Adrian Will / adrian.will.01@gmail.com Sebastian Rodriguez / sebastian.rodriguez@gitia.org Introduction 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) Documentation - Example //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(); Maven - jitpack.io 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> 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/ ) License Froog is released under the Apache 2 open source license.
