public void TrainClassifier(DataTable table)
{
dataSet2.Tables.Add(table);
DataTable GaussianDistribution = dataSet2.Tables.Add("Gaussian");
GaussianDistribution.Columns.Add(table.Columns[0].ColumnName);
for (int i = 1; i < table.Columns.Count; i++)
{
GaussianDistribution.Columns.Add(table.Columns[i].ColumnName + "Mean");
GaussianDistribution.Columns.Add(table.Columns[i].ColumnName + "Variance");
}
var results = (from myRow in table.AsEnumerable()
group myRow by myRow.Field <string>(table.Columns[0].ColumnName) into g
select new { Name = g.Key, Count = g.Count() }).ToList();
for (int j = 0; j < results.Count; j++)
{
DataRow row = GaussianDistribution.Rows.Add();
row[0] = results[j].Name;
int a = 1;
for (int i = 1; i < table.Columns.Count; i++)
{
row[a] = VarianceAndMean.Mean(SelectRows(table, i, string.Format("{0} = '{1}'", table.Columns[0].ColumnName, results[j].Name)));
row[++a] = VarianceAndMean.Variance(SelectRows(table, i, string.Format("{0} = '{1}'", table.Columns[0].ColumnName, results[j].Name)));
a++;
}
}
}
//الميثود الخاص بعملية تدريب الخوارزمية على البيانات
public void TrainClassifier(DataTable table2)
{
dataSet.Tables.Add(table2);
//table
//استخدام التوزع الغوصي
DataTable GaussianDistribution = dataSet.Tables.Add("Gaussian");
GaussianDistribution.Columns.Add(table2.Columns[0].ColumnName);
//columns
for (int i = 1; i < table2.Columns.Count; i++)
{
GaussianDistribution.Columns.Add(table2.Columns[i].ColumnName + "Mean");
GaussianDistribution.Columns.Add(table2.Columns[i].ColumnName + "Variance");
}
//calc data
var results = (from myRow in table2.AsEnumerable()
group myRow by myRow.Field <string>(table2.Columns[0].ColumnName) into g
select new { Name = g.Key, Count = g.Count() }).ToList();
for (int j = 0; j < results.Count; j++)
{
DataRow row = GaussianDistribution.Rows.Add();
row[0] = results[j].Name;
int a = 1;
for (int i = 1; i < table2.Columns.Count; i++)
{
//حساب التبياين
row[a] = VarianceAndMean.Mean(SelectRows(table2, i, string.Format("{0} = '{1}'", table2.Columns[0].ColumnName, results[j].Name)));
//حساب المتوسط الحسابي
row[++a] = VarianceAndMean.Variance(SelectRows(table2, i, string.Format("{0} = '{1}'", table2.Columns[0].ColumnName, results[j].Name)));
a++;
}
}
}