Examples of tv.floe.metronome.deeplearning.neuralnetwork.core.LogisticRegression.predict()

tv.floe.metronome.deeplearning.neuralnetwork.core.LogisticRegression.predict()
Classify input @param x the input (can either be a matrix or vector)If it's a matrix, each row is considered an example and associated rows are classified accordingly. Each row will be the likelihood of a label given that example @return a probability distribution for each row

    LogisticRegressionOptimizer opt = new LogisticRegressionOptimizer( logreg, learningRate );
    CustomConjugateGradient g = new CustomConjugateGradient(opt);
    g.optimize();
    
    
    Matrix predict = logreg.predict(x);
    //log.info(predict.toString());


    Evaluation eval = new Evaluation();
    eval.eval(y, predict);
    //log.info(eval.stats());

View Full Code Here

        
        CustomConjugateGradient g = new CustomConjugateGradient(opt);
        g.optimize();
        
        
        Matrix predict = logreg.predict(xMatrix);
        //log.info(predict.toString());


        Evaluation eval = new Evaluation();
        eval.eval(yMatrix, predict);
        //log.info(eval.stats());

View Full Code Here

    //NonZeroStoppingConjugateGradient g = new NonZeroStoppingConjugateGradient(opt);
    g.optimize();
    
    
    
    Matrix predict = logRegression.predict(input);


    Evaluation eval = new Evaluation();
    eval.eval(labels, predict);
    //log.info(eval.stats());
    System.out.println( eval.stats() );

View Full Code Here

      //logRegression.trainWithAdagrad(x, y);
      logRegression.train(x_xor_Matrix, y_xor_Matrix, 0.001);


    }
    
    Matrix predictions = logRegression.predict(x_xor_Matrix);
    
    MatrixUtils.debug_print(predictions);
    


    //Matrix predict = logRegression.predict(x);

View Full Code Here


    }
    
//    Matrix predictions = logRegression.predict(xTestMatrix);
    
    Matrix predict = logRegression.predict(xMatrix);
    //log.info(predict.toString());


    Evaluation eval = new Evaluation();
    eval.eval(yMatrix, predict);
    //log.info(eval.stats());

View Full Code Here


    }
    
//    Matrix predictions = logRegression.predict(xTestMatrix);
    
    Matrix predict = logRegression.predict(input);
    //log.info(predict.toString());


    Evaluation eval = new Evaluation();
    eval.eval(labels, predict);
    //log.info(eval.stats());

View Full Code Here


    }
    
//    Matrix predictions = logRegression.predict(xTestMatrix);
    
    Matrix predict = logRegression.predict(input);
    //log.info(predict.toString());


    Evaluation eval = new Evaluation();
    eval.eval(labels, predict);
    //log.info(eval.stats());

View Full Code Here

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.