@Override public void timesEquals( DiagonalMatrix matrix) { if( !this.checkSameDimensions(matrix) ) { throw new IllegalArgumentException( "Matrix must be the same size as this" ); } final int M = this.getDimensionality(); // The diagonal elements scale each row for( int i = 0; i < M; i++ ) { final double d1i = this.getElement(i); final double d2j = matrix.getElement(i); final double v = d1i * d2j; this.setElement(i, v); } }
final double r = yhat*(1.0-yhat); this.err.setElement( n, (y - yhat) ); this.R.setElement( n, r ); this.Ri.setElement( n, (r!=0.0) ? 1.0/r : 0.0 ); n++; z.plusEquals( this.Ri.times( this.err ) ); this.R.timesEquals(this.W); Matrix lhs = this.X.times( this.R.times( this.Xt ) ); if( this.regularization != 0.0 ) Vector rhs = this.X.times( this.R.times( z ) );
this.W.setElement( n, DatasetUtil.getWeight(sample) ); n++;
beta); final Matrix varianceInverse = target.getCovariance().inverse(); varianceInverse.plusEquals(varianceInverseUpdate); final Matrix covariance = varianceInverse.inverse();
this.W.setElement( n, DatasetUtil.getWeight(sample) ); n++;
beta); final Matrix varianceInverse = target.getCovariance().inverse(); varianceInverse.plusEquals(varianceInverseUpdate); final Matrix covariance = varianceInverse.inverse();
final double r = yhat*(1.0-yhat); this.err.setElement( n, (y - yhat) ); this.R.setElement( n, r ); this.Ri.setElement( n, (r!=0.0) ? 1.0/r : 0.0 ); n++; z.plusEquals( this.Ri.times( this.err ) ); this.R.timesEquals(this.W); Matrix lhs = this.X.times( this.R.times( this.Xt ) ); if( this.regularization != 0.0 ) Vector rhs = this.X.times( this.R.times( z ) );
@Override public void timesEquals( DiagonalMatrix matrix) { if( !this.checkSameDimensions(matrix) ) { throw new IllegalArgumentException( "Matrix must be the same size as this" ); } final int M = this.getDimensionality(); // The diagonal elements scale each row for( int i = 0; i < M; i++ ) { final double d1i = this.getElement(i); final double d2j = matrix.getElement(i); final double v = d1i * d2j; this.setElement(i, v); } }
this.W.setElement( n, DatasetUtil.getWeight(sample) ); n++;
beta); final Matrix varianceInverse = target.getCovariance().inverse(); varianceInverse.plusEquals(varianceInverseUpdate); final Matrix covariance = varianceInverse.inverse();
final double r = yhat*(1.0-yhat); this.err.setElement( n, (y - yhat) ); this.R.setElement( n, r ); this.Ri.setElement( n, (r!=0.0) ? 1.0/r : 0.0 ); n++; z.plusEquals( this.Ri.times( this.err ) ); this.R.timesEquals(this.W); Matrix lhs = this.X.times( this.R.times( this.Xt ) ); if( this.regularization != 0.0 ) Vector rhs = this.X.times( this.R.times( z ) );
@Override public void timesEquals( DiagonalMatrix matrix) { if( !this.checkSameDimensions(matrix) ) { throw new IllegalArgumentException( "Matrix must be the same size as this" ); } final int M = this.getDimensionality(); // The diagonal elements scale each row for( int i = 0; i < M; i++ ) { final double d1i = this.getElement(i); final double d2j = matrix.getElement(i); final double v = d1i * d2j; this.setElement(i, v); } }