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The "MultiLayerPerceptron" page has been changed by YexiJiang: https://wiki.apache.org/hama/MultiLayerPerceptron?action=diff&rev1=26&rev2=27 The following is the sample code regarding model initialization. {{{ - String modelPath = "/tmp/xorModel-training-by-xor.data"; - double learningRate = 0.6; - double regularization = 0.02; // no regularization - double momentum = 0.3; // no momentum - String squashingFunctionName = "Tanh"; - String costFunctionName = "SquaredError"; - int[] layerSizeArray = new int[] { 2, 5, 1 }; - SmallMultiLayerPerceptron mlp = new SmallMultiLayerPerceptron(learningRate, - regularization, momentum, squashingFunctionName, costFunctionName, - layerSizeArray); + SmallLayeredNeuralNetwork ann = new SmallLayeredNeuralNetwork(); + + ann.setLearningRate(0.1); // set the learning rate + ann.setMomemtumWeight(0.1); // set the momemtum weight + + // initialize the topology of the model, a three-layer model is created in this example + ann.addLayer(featureDimension, false, FunctionFactory.createDoubleFunction("Sigmoid")); + ann.addLayer(featureDimension, false, FunctionFactory.createDoubleFunction("Sigmoid")); + ann.addLayer(labelDimension, true, FunctionFactory.createDoubleFunction("Sigmoid")); + + // set the cost function to evaluate the error + ann.setCostFunction(FunctionFactory.createDoubleDoubleFunction("CrossEntropy")); + String trainedModelPath = ...; + ann.setModelPath(trainedModelPath); // set the path to store the trained model + + // add training parameters + Map<String, String> trainingParameters = new HashMap<String, String>(); + trainingParameters.put("tasks", "5"); // the number of concurrent tasks + trainingParameters.put("training.max.iterations", "" + iteration); // the number of maximum iterations + trainingParameters.put("training.batch.size", "300"); // the number of training instances read per update + ann.train(new Path(trainingDataPath), trainingParameters); }}} === Two class learning problem ===
