#region License Information
/* HeuristicLab
* Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
namespace HeuristicLab.DataPreprocessing {
public class TransformationLogic : ITransformationLogic {
private readonly ITransactionalPreprocessingData preprocessingData;
private readonly ISearchLogic searchLogic;
private readonly IStatisticsLogic statisticsLogic;
public TransformationLogic(ITransactionalPreprocessingData thePreprocessingData, ISearchLogic theSearchLogic, IStatisticsLogic theStatisticsLogic) {
preprocessingData = thePreprocessingData;
searchLogic = theSearchLogic;
statisticsLogic = theStatisticsLogic;
}
public void DeleteRowsWithMissingValuesGreater(double percent) {
for (int i = 0; i < preprocessingData.Rows; ++i) {
int missingCount = statisticsLogic.GetRowMissingValueCount(i);
if (100f / preprocessingData.Columns * missingCount >= percent) {
preprocessingData.DeleteRow(i);
--i;
}
}
}
public void DeleteColumnsWithMissingValuesGreater(float percent) {
for (int i = 0; i < preprocessingData.Columns; ++i) {
int missingCount = statisticsLogic.GetMissingValueCount(i);
if (100f / preprocessingData.Columns * missingCount >= percent) {
preprocessingData.DeleteColumn(i);
--i;
}
}
}
public void DeleteColumnsWithVarianceSmaller(double variance) {
for (int i = 0; i < preprocessingData.Columns; ++i) {
if (preprocessingData.IsType(i) || preprocessingData.IsType(i)) {
double columnVariance = statisticsLogic.GetVariance(i);
if (columnVariance < variance) {
preprocessingData.DeleteColumn(i);
--i;
}
}
}
}
}
}