Example usage for org.apache.mahout.classifier.sgd OnlineLogisticRegression stepOffset

Introduction

In this page you can find the example usage for org.apache.mahout.classifier.sgd OnlineLogisticRegression stepOffset.

Prototype

int stepOffset

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Usage

From source file:org.wso2.siddhi.extension.ModelInitializer.java

License:Open Source License

public static OnlineLogisticRegression InitializeLogisticRegression(String modelPath) {
    OnlineLogisticRegression LRmodel = null;
    FileInputStream fileInputStream = null;
    ObjectInputStream objectInputStream = null;
    double[][] modelWeights = null;
    LogisticRegressionModel LRmodelObject;
    try {/*ww  w .j a  v  a2s .c o  m*/
        // get the values for hyper-parameters from model file.
        fileInputStream = new FileInputStream(modelPath);
        objectInputStream = new ObjectInputStream(fileInputStream);
        LRmodelObject = (LogisticRegressionModel) objectInputStream.readObject();
        LRmodel = new OnlineLogisticRegression(LRmodelObject.getNumCategories(), LRmodelObject.getNumFeatures(),
                new L2(1));
        LRmodel.learningRate(LRmodelObject.getLearningRate());
        LRmodel.lambda(LRmodelObject.getLambda());
        LRmodel.alpha(LRmodelObject.getAlpha());
        LRmodel.stepOffset(LRmodelObject.getStepOffset());
        LRmodel.decayExponent(LRmodelObject.getDecayExponent());
        modelWeights = LRmodelObject.getWeights();
        fileInputStream.close();
        objectInputStream.close();
        for (int i = 0; i < modelWeights.length; i++) {
            for (int j = 0; j < modelWeights[0].length; j++) {
                LRmodel.setBeta(i, j, modelWeights[i][j]);
            }
        }
    } catch (Exception e) {
        logger.error("Failed to create a Logistic Regression model from the file \"" + modelPath + "\"", e);
    } finally {
        try {
            fileInputStream.close();
            objectInputStream.close();
        } catch (IOException e) {
            logger.error("Failed to close the model input stream!", e);
        }
    }
    logger.info("Logistic Regression model execution plan successfully intialized for \"" + modelPath
            + "\" model file.");
    return LRmodel;
}

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