protected void cleanupAlgorithm() { if (this.getSupportsMap() != null) { // Make the result object have a more efficient backing collection // at the end. this.getResult().setExamples( new ArrayList<WeightedValue<InputType>>( this.getSupportsMap().values() ) ); this.setSupportsMap( null ); } }
protected void cleanupAlgorithm() { if (this.getSupportsMap() != null) { // Make the result object have a more efficient backing collection // at the end. this.getResult().setExamples( new ArrayList<WeightedValue<InputType>>( this.getSupportsMap().values() ) ); this.setSupportsMap( null ); } }
protected void cleanupAlgorithm() { if (this.getSupportsMap() != null) { // Make the result object have a more efficient backing collection // at the end. this.getResult().setExamples( new ArrayList<WeightedValue<InputType>>( this.getSupportsMap().values() ) ); this.setSupportsMap( null ); } }
protected boolean initializeAlgorithm() { if (this.getData() == null) { // Error: No data to learn on. return false; } // Count the number of valid examples. int validCount = 0; for (InputOutputPair<? extends InputType, Double> example : this.getData()) { if (example != null) { validCount++; } } if (validCount <= 0) { // Nothing to perform learning on. return false; } // Set up the learning variables. this.setErrorCount( validCount ); this.setSupportsMap( new LinkedHashMap<InputOutputPair<? extends InputType, Double>, DefaultWeightedValue<InputType>>() ); this.setResult( new KernelScalarFunction<InputType>( this.getKernel(), this.getSupportsMap().values(), 0.0 ) ); return true; }
protected boolean initializeAlgorithm() { if (this.getData() == null) { // Error: No data to learn on. return false; } // Count the number of valid examples. int validCount = 0; for (InputOutputPair<? extends InputType, Double> example : this.getData()) { if (example != null) { validCount++; } } if (validCount <= 0) { // Nothing to perform learning on. return false; } // Set up the learning variables. this.setErrorCount( validCount ); this.setSupportsMap( new LinkedHashMap<InputOutputPair<? extends InputType, Double>, DefaultWeightedValue<InputType>>() ); this.setResult( new KernelScalarFunction<InputType>( this.getKernel(), this.getSupportsMap().values(), 0.0 ) ); return true; }
protected boolean initializeAlgorithm() { if (this.getData() == null) { // Error: No data to learn on. return false; } // Count the number of valid examples. int validCount = 0; for (InputOutputPair<? extends InputType, Double> example : this.getData()) { if (example != null) { validCount++; } } if (validCount <= 0) { // Nothing to perform learning on. return false; } // Set up the learning variables. this.setErrorCount( validCount ); this.setSupportsMap( new LinkedHashMap<InputOutputPair<? extends InputType, Double>, DefaultWeightedValue<InputType>>() ); this.setResult( new KernelScalarFunction<InputType>( this.getKernel(), this.getSupportsMap().values(), 0.0 ) ); return true; }
@Override public KernelBasedIterativeRegression<InputType> clone() { KernelBasedIterativeRegression<InputType> clone = (KernelBasedIterativeRegression<InputType>) super.clone(); clone.setKernel( ObjectUtil.cloneSmart( this.getKernel() ) ); clone.setResult( ObjectUtil.cloneSafe( this.getResult() ) ); clone.setSupportsMap( ObjectUtil.cloneSmart( this.getSupportsMap() ) ); return clone; }
@Override public KernelBasedIterativeRegression<InputType> clone() { KernelBasedIterativeRegression<InputType> clone = (KernelBasedIterativeRegression<InputType>) super.clone(); clone.setKernel( ObjectUtil.cloneSmart( this.getKernel() ) ); clone.setResult( ObjectUtil.cloneSafe( this.getResult() ) ); clone.setSupportsMap( ObjectUtil.cloneSmart( this.getSupportsMap() ) ); return clone; }
@Override public KernelBasedIterativeRegression<InputType> clone() { KernelBasedIterativeRegression<InputType> clone = (KernelBasedIterativeRegression<InputType>) super.clone(); clone.setKernel( ObjectUtil.cloneSmart( this.getKernel() ) ); clone.setResult( ObjectUtil.cloneSafe( this.getResult() ) ); clone.setSupportsMap( ObjectUtil.cloneSmart( this.getSupportsMap() ) ); return clone; }