public decimal[] GetMaxVector()
{
var maxVector = new decimal[NumberOfColumns];
for (int i = 0; i < NumberOfColumns; i++)
{
maxVector[i] = DecisionRows.Max(row => row.DecisionValues[i]);
}
return(maxVector);
}
public List <DecisionColumn> CalculateDecisions()
{
DecisionColumns = new List <DecisionColumn>();
for (int i = 0; i < DecisionRows.First().Length - 1; i++)
{
var decisionColumn = new DecisionColumn();
var uniqueValues = DecisionRows.Select(value => value[i]).Distinct().ToList();
foreach (var uniqueValue in uniqueValues)
{
var decisionAttributeOccurence = new DecisionAttributeOccurence(uniqueValue);
for (int j = 0; j < DecisionRows.Count; j++)
{
if (DecisionRows[j][i] == uniqueValue)
{
var lastColumnDecision = LastRowOccurences.Where(occurence => occurence.RowNumbers.Contains(j + 1)).Select(occurence => occurence.Decision).First();
if (lastColumnDecision == DecisionType.Positive)
{
decisionAttributeOccurence.PositiveRowNumbers.Add(j + 1);
}
else
{
decisionAttributeOccurence.NegativeRowNumbers.Add(j + 1);
}
}
}
decisionColumn.Attributes.Add(decisionAttributeOccurence);
}
DecisionColumns.Add(decisionColumn);
}
CalculateColumnsEntropies();
CalculateColumnInformationGain();
var rejectedList = DecisionColumns.Where(column => AlreadyUsedIndexes.Contains((int)column.ColumnIndex));
var bestOne = DecisionColumns.Except(rejectedList).MaxBy(column => column.InformationGain); //Nieużyta z największym przyrostem informacji
var indexes = new List <int> {
(int)bestOne.ColumnIndex
};
DoUnknownThing(indexes, null);
return(DecisionColumns);
}
