//INPUT : get list of H(fi)
//PROCESS : select 1 candidate, return col name
public static string select1Candidate_entropy(int method, DataTable dt,
List <string> list_F, List <string> list_S
, List <str_double> list_entropy, List <str2_double> list_MI)
{
List <string> list_predict = new List <string>();
list_predict.AddRange(list_S);
try
{
temp_listEntropy.Clear();
temp_colWithHigestEntropy = "";
double highestQuality = -9999;
foreach (string f in list_F)
{
//----- test 1 candidate ---------
list_predict.Add(f);
str_double new_data = new str_double();
new_data.str = f;
if (method == methodSelection_Greedy)
{
new_data.v = calJointEntropy(dt, list_predict);
} //target
else if (method == methodSelection_MIFS)
{
new_data.v = candidate_calMIFS(dt, f, list_S, list_entropy, list_MI);
}
else if (method == methodSelection_JMIM)
{
new_data.v = candidate_calMAXIMIN(miximinMethod_JMIM, dt, f, list_S, list_entropy, list_MI);
}
else if (method == methodSelection_CMIM)
{
new_data.v = candidate_calMAXIMIN(miximinMethod_CMIM, dt, f, list_S, list_entropy, list_MI);
}
temp_listEntropy.Add(new_data);
if (new_data.v > highestQuality)
{
temp_colWithHigestEntropy = new_data.str;
highestQuality = new_data.v;
}
list_predict.RemoveAt(list_predict.Count - 1);
}
}
catch (Exception ex) { TheSys.showError(ex); temp_colWithHigestEntropy = ""; }
return(temp_colWithHigestEntropy);
}
public static str_double calEntropyOfColumn(DataTable dt, DataColumn dc)
{
str_double entropy = new str_double();
try
{
//--- build unique list ------------------------------------------------
List <str_int> list_unique = new List <str_int>();
foreach (DataRow dr in dt.Rows)
{
Boolean neverExist = true;
string current_v = dr[dc].ToString();
foreach (str_int uni in list_unique)
{
if (uni.str == current_v)
{
uni.i++; neverExist = false; break;
}
}
if (neverExist)
{
list_unique.Add(new str_int()
{
str = current_v, i = 1
});
}
}
//--- Compute Entropy ------------------------------------------------
double prob_log_cummulative = 0;
int total_row = dt.Rows.Count;
foreach (str_int uni in list_unique)
{
prob_log_cummulative += calPossibleLog(uni.i, total_row);
}
entropy.str = dc.ColumnName;
entropy.v = -prob_log_cummulative;
}
catch (Exception ex) { TheSys.showError(ex); }
return(entropy);
}
//Threshold End - Start
//public static Feature getFeature(string selected_feature, DataTable dt)
//{
// Feature f = new Feature();
// f.name = selected_feature;
// try
// {
// double start = TheTool.getDouble(dt.Rows[0][selected_feature].ToString());
// double end = TheTool.getDouble(dt.Rows[dt.Rows.Count - 1][selected_feature].ToString());
// if (end > start) { f.opt = ">="; }
// else { f.opt = "<="; }
// //-----
// start = Math.Round(start, 2);
// end = Math.Round(end, 2);
// double v = (start + end) / 2;
// f.v = Math.Round(v, 2);
// }
// catch (Exception ex) { TheSys.showError(ex); }
// return f;
//}
////indices is row number
//public static Feature getFeature(string selected_feature, DataTable dt_concat
// , List<int> start_indices, List<int> end_indices)
//{
// Feature f = new Feature();
// f.name = selected_feature;
// try
// {
// double start = TheTool.dataTable_getAverage(dt_concat, start_indices, selected_feature);
// double end = TheTool.dataTable_getAverage(dt_concat, end_indices, selected_feature);
// if (end > start) { f.opt = ">="; }
// else { f.opt = "<="; }
// //-----
// start = Math.Round(start, 2);
// end = Math.Round(end, 2);
// double v = (start + end) / 2;
// f.v = Math.Round(v, 2);
// }
// catch (Exception ex) { TheSys.showError(ex); }
// return f;
//}
////Feature Name with Threshold by DataTable (First - End)
//public static Feature getFeature(string s)
//{
// Feature f = new Feature();
// f.name = s;
// return f;
//}
//public static List<string> Feature_getListName(List<Feature> list_f)
//{
// List<string> list = new List<string>();
// foreach (Feature f in list_f) { list.Add(f.name); }
// return list;
//}
//public static List<string> Feature_getListFullString(List<Feature> list_f)
//{
// List<string> list = new List<string>();
// foreach (Feature f in list_f) { list.Add(f.name + " " + f.opt + " " + f.v); }
// return list;
//}
//H(X)
//table contain only useful Column, value are discretized
//analyze all row
public static List <str_double> calEntropy(DataTable dt)
{
List <str_double> list_entropy = new List <str_double>();
List <string> final_output = new List <string>();//Data
try
{
double highestEntropy = 0;
foreach (DataColumn dc in dt.Columns)
{
str_double new_data = calEntropyOfColumn(dt, dc);
list_entropy.Add(new_data);
if (new_data.v > highestEntropy)
{
temp_colWithHigestEntropy = new_data.str;
highestEntropy = new_data.v;
}
}
}
catch (Exception ex) { TheSys.showError(ex); temp_colWithHigestEntropy = ""; }
return(list_entropy);
}