public static void BulidTree(DecisionTreeNode currentNode, Dictionary <string, string> searchedColumns, List <DataRow> rows)
{
List <DataRow> tempRows = new List <DataRow>(rows);
string decColumn = Dt.Columns[Dt.Columns.Count - 1].ColumnName;
var decisions = tempRows.Select(d => d.Field <string>(decColumn))
.Distinct().ToList();
//Przefiltrowanie tablicy w zależności od poprzednich atrybutów
foreach (var data in searchedColumns)
{
tempRows = tempRows.Where(i => (string)i[data.Key] == data.Value).ToList();
}
//obliczanie I(X)
var decisionCount = tempRows
.GroupBy(row => row.Field <string>(decColumn)).ToDictionary(g => g.Key, g => g.Count());
NormalizeDictionary(decisionCount, decisions);
double iValue = CalculateGain(decisionCount);
//warunek stopu
if (iValue == 0)
{
var decision = decisionCount.Where(i => i.Value != 0).Select(i => i.Key).FirstOrDefault();
currentNode.Attribute = decision;
currentNode.IsDecision = true;
return;
}
else if (GetColumnsWithoutLast().Count == searchedColumns.Count)
{
var decision = decisionCount.Where(i => i.Value == decisionCount.Max(x => x.Value)).Select(i => i.Key).FirstOrDefault();
currentNode.Attribute = decision;
currentNode.IsDecision = true;
return;
}
else
{
Dictionary <string, double> atrrGains = new Dictionary <string, double>();
//Wybór atrybutu
foreach (string column in GetColumnsWithoutLast().Where(i => !searchedColumns.Keys.Contains(i)))
{
var values = rows.Select(d => d.Field <string>(column))
.Distinct();
List <GainData> gainWithTotalValues = new List <GainData>();
foreach (var value in values)
{
var decisionCountForAttributes = tempRows
.Where(i => (string)i[column] == value)
.GroupBy(row => row.Field <string>(decColumn)).ToDictionary(g => g.Key, g => g.Count());
NormalizeDictionary(decisionCountForAttributes, decisions);
double maxCount = decisionCountForAttributes.Sum(i => i.Value);
gainWithTotalValues.Add(new GainData
{
TotalValues = maxCount,
Gain = CalculateGain(decisionCountForAttributes)
});
}
double totalGain = 0;
foreach (var val in gainWithTotalValues)
{
totalGain += (val.TotalValues / gainWithTotalValues.Sum(i => i.TotalValues)) * val.Gain;
}
totalGain = iValue - totalGain;
atrrGains.Add(column, totalGain);
}
if (atrrGains.Count() == 0)
{
}
var bestAttribute = atrrGains.Where(i => i.Value == atrrGains.Max(x => x.Value)).FirstOrDefault().Key;
currentNode.Attribute = bestAttribute;
currentNode.IsDecision = false;
foreach (var value in rows.Select(d => d.Field <string>(bestAttribute))
.Distinct())
{
var tempSearched = new Dictionary <string, string>(searchedColumns);
tempSearched.Add(bestAttribute, value);
DecisionTreeNode child = new DecisionTreeNode();
currentNode.LinkedNodes.Add(value, child);
BulidTree(child, tempSearched, rows);
}
}
}
public static void BeginBulidTree()
{
DecisionTreeRoot = new DecisionTreeNode();
BulidTree(DecisionTreeRoot, new Dictionary <string, string>(), Dt.Rows.Cast <DataRow>().ToList());
}
