Examples with SigmoidPerceptron org.knime.base.data.neural.SigmoidPerceptron used on opensource projects

Example 1 with SigmoidPerceptron

use of org.knime.base.data.neural.SigmoidPerceptron in project knime-core by knime.

the class PMMLNeuralNetworkTranslator method initiateFinalLayer.

/**
 * @param nnModel
 *            the PMML neural network model
 */
private void initiateFinalLayer(final NeuralNetwork nnModel) {
    NeuralLayer hiddenLayer = nnModel.getNeuralLayerArray(nnModel.getNeuralLayerArray().length - 1);
    m_counter = 0;
    m_idPosMap = new HashMap<String, Integer>();
    m_curLayer++;
    m_curPerceptrons = new Vector<Perceptron>();
    for (Neuron neuron : hiddenLayer.getNeuronArray()) {
        m_weights = new double[m_predPerceptrons.length];
        m_curPercpetronID = neuron.getId();
        m_curThreshold = -1 * neuron.getBias();
        for (Con con : neuron.getConArray()) {
            String fromID = con.getFrom();
            double weight = con.getWeight();
            int pos = m_predidPosMap.get(fromID);
            m_weights[pos] = weight;
        }
        Perceptron p = new SigmoidPerceptron(m_weights, m_predPerceptrons);
        p.setThreshold(m_curThreshold);
        m_curPerceptrons.add(p);
        m_idPosMap.put(m_curPercpetronID, m_counter);
        m_counter++;
    }
    Perceptron[] curPerceptrons = new Perceptron[m_curPerceptrons.size()];
    curPerceptrons = m_curPerceptrons.toArray(curPerceptrons);
    m_allLayers.add(m_curLayer, new HiddenLayer(m_predLayer, curPerceptrons));
    m_predLayer = m_allLayers.get(m_curLayer);
    m_predPerceptrons = curPerceptrons;
    m_predidPosMap = new HashMap<String, Integer>(m_idPosMap);
}

Example 2 with SigmoidPerceptron

use of org.knime.base.data.neural.SigmoidPerceptron in project knime-core by knime.

the class PMMLNeuralNetworkTranslator method initiateFinalLayer.

/**
 * @param nnModel
 *            the PMML neural network model
 */
private void initiateFinalLayer(final NeuralNetwork nnModel) {
    NeuralLayer hiddenLayer = nnModel.getNeuralLayerArray(nnModel.getNeuralLayerArray().length - 1);
    m_counter = 0;
    m_idPosMap = new HashMap<String, Integer>();
    m_curLayer++;
    m_curPerceptrons = new Vector<Perceptron>();
    for (Neuron neuron : hiddenLayer.getNeuronArray()) {
        m_weights = new double[m_predPerceptrons.length];
        m_curPercpetronID = neuron.getId();
        m_curThreshold = -1 * neuron.getBias();
        for (Con con : neuron.getConArray()) {
            String fromID = con.getFrom();
            double weight = con.getWeight();
            int pos = m_predidPosMap.get(fromID);
            m_weights[pos] = weight;
        }
        Perceptron p = new SigmoidPerceptron(m_weights, m_predPerceptrons);
        p.setThreshold(m_curThreshold);
        m_curPerceptrons.add(p);
        m_idPosMap.put(m_curPercpetronID, m_counter);
        m_counter++;
    }
    Perceptron[] curPerceptrons = new Perceptron[m_curPerceptrons.size()];
    curPerceptrons = m_curPerceptrons.toArray(curPerceptrons);
    m_allLayers.add(m_curLayer, new HiddenLayer(m_predLayer, curPerceptrons));
    m_predLayer = m_allLayers.get(m_curLayer);
    m_predPerceptrons = curPerceptrons;
    m_predidPosMap = new HashMap<String, Integer>(m_idPosMap);
}

Example 3 with SigmoidPerceptron

use of org.knime.base.data.neural.SigmoidPerceptron in project knime-core by knime.

the class PMMLNeuralNetworkTranslator method initiateHiddenLayers.

/**
 * @param nnModel the PMML neural network model
 */
private void initiateHiddenLayers(final NeuralNetwork nnModel) {
    for (int i = 0; i < nnModel.getNeuralLayerArray().length - 1; i++) {
        NeuralLayer hiddenLayer = nnModel.getNeuralLayerArray(i);
        m_counter = 0;
        m_idPosMap = new HashMap<String, Integer>();
        m_curLayer++;
        m_curPerceptrons = new Vector<Perceptron>();
        for (Neuron neuron : hiddenLayer.getNeuronArray()) {
            m_weights = new double[m_predPerceptrons.length];
            m_curPercpetronID = neuron.getId();
            m_curThreshold = -1 * neuron.getBias();
            for (Con con : neuron.getConArray()) {
                String fromID = con.getFrom();
                double weight = con.getWeight();
                int pos = m_predidPosMap.get(fromID);
                m_weights[pos] = weight;
            }
            Perceptron p = new SigmoidPerceptron(m_weights, m_predPerceptrons);
            p.setThreshold(m_curThreshold);
            m_curPerceptrons.add(p);
            m_idPosMap.put(m_curPercpetronID, m_counter);
            m_counter++;
        }
        Perceptron[] curPerceptrons = new Perceptron[m_curPerceptrons.size()];
        curPerceptrons = m_curPerceptrons.toArray(curPerceptrons);
        m_allLayers.add(m_curLayer, new HiddenLayer(m_predLayer, curPerceptrons));
        m_predLayer = m_allLayers.get(m_curLayer);
        m_predPerceptrons = curPerceptrons;
        m_predidPosMap = new HashMap<String, Integer>(m_idPosMap);
    }
}

Example 4 with SigmoidPerceptron

use of org.knime.base.data.neural.SigmoidPerceptron in project knime-core by knime.

the class PMMLNeuralNetworkTranslator method initiateHiddenLayers.

/**
 * @param nnModel the PMML neural network model
 */
private void initiateHiddenLayers(final NeuralNetwork nnModel) {
    for (int i = 0; i < nnModel.getNeuralLayerArray().length - 1; i++) {
        NeuralLayer hiddenLayer = nnModel.getNeuralLayerArray(i);
        m_counter = 0;
        m_idPosMap = new HashMap<String, Integer>();
        m_curLayer++;
        m_curPerceptrons = new Vector<Perceptron>();
        for (Neuron neuron : hiddenLayer.getNeuronArray()) {
            m_weights = new double[m_predPerceptrons.length];
            m_curPercpetronID = neuron.getId();
            m_curThreshold = -1 * neuron.getBias();
            for (Con con : neuron.getConArray()) {
                String fromID = con.getFrom();
                double weight = con.getWeight();
                int pos = m_predidPosMap.get(fromID);
                m_weights[pos] = weight;
            }
            Perceptron p = new SigmoidPerceptron(m_weights, m_predPerceptrons);
            p.setThreshold(m_curThreshold);
            m_curPerceptrons.add(p);
            m_idPosMap.put(m_curPercpetronID, m_counter);
            m_counter++;
        }
        Perceptron[] curPerceptrons = new Perceptron[m_curPerceptrons.size()];
        curPerceptrons = m_curPerceptrons.toArray(curPerceptrons);
        m_allLayers.add(m_curLayer, new HiddenLayer(m_predLayer, curPerceptrons));
        m_predLayer = m_allLayers.get(m_curLayer);
        m_predPerceptrons = curPerceptrons;
        m_predidPosMap = new HashMap<String, Integer>(m_idPosMap);
    }
}