weights = log(sequence(1, mu, 1)).scalarMultiply(-1).scalarAdd(logMu2); double sumw = 0; double sumwq = 0;
weights = log(sequence(1, mu, 1)).scalarMultiply(-1).scalarAdd(logMu2); double sumw = 0; double sumwq = 0;
RealMatrix gammaShpNext = MatrixUtils.createRealMatrix(userNum, featureCount); RealMatrix lambdaShpNext = MatrixUtils.createRealMatrix(itemNum, featureCount); gammaShpNext = gammaShpNext.scalarAdd(a); lambdaShpNext = lambdaShpNext.scalarAdd(c); RealVector phiUI = MatrixUtils.createRealVector(new double[featureCount]);
public Matrix plus(double value) { Matrix result = CommonsMathDenseDoubleMatrix2DFactory.INSTANCE.dense(matrix.scalarAdd(value)); MapMatrix<String, Object> a = getMetaData(); if (a != null) { result.setMetaData(a.clone()); } return result; }
public Matrix minus(double value) { Matrix result = CommonsMathDenseDoubleMatrix2DFactory.INSTANCE.dense(matrix.scalarAdd(-value)); MapMatrix<String, Object> a = getMetaData(); if (a != null) { result.setMetaData(a.clone()); } return result; }
public Matrix minus(double value) { Matrix result = CommonsMathDenseDoubleMatrix2DFactory.INSTANCE.dense(matrix.scalarAdd(-value)); MapMatrix<String, Object> a = getMetaData(); if (a != null) { result.setMetaData(a.clone()); } return result; }
public Matrix plus(double value) { Matrix result = CommonsMathDenseDoubleMatrix2DFactory.INSTANCE.dense(matrix.scalarAdd(value)); MapMatrix<String, Object> a = getMetaData(); if (a != null) { result.setMetaData(a.clone()); } return result; }
final RealMatrix L2 = MatrixUtils.multiplyElements(L,L).scalarAdd(delta); final double[] rowSums = new double[p];
weights = log(sequence(1, mu, 1)).scalarMultiply(-1).scalarAdd(logMu2); double sumw = 0; double sumwq = 0;
newGenotype = newGenotype.scalarAdd(-1.0);
weights = log(sequence(1, mu, 1)).scalarMultiply(-1).scalarAdd(logMu2); double sumw = 0; double sumwq = 0;
weights = log(sequence(1, mu, 1)).scalarMultiply(-1).scalarAdd(logMu2); double sumw = 0; double sumwq = 0;