public void getMlrModel(string modelPath, bool BuildModel = false)
{
using (System.IO.StreamReader sr = new System.IO.StreamReader(modelPath))
{
string mType = sr.ReadLine();
modelTypes m = (modelTypes)Enum.Parse(typeof(modelTypes), mType);
if (m != modelTypes.MvlRegression)
{
System.Windows.Forms.MessageBox.Show("Model file specified is not a Multivariate Linear Regression Model!!", "Error", System.Windows.Forms.MessageBoxButtons.OK, System.Windows.Forms.MessageBoxIcon.Error);
return;
}
string ln = sr.ReadLine();
List <dataPrepLinearReg> lrLst = new List <dataPrepLinearReg>();
while (ln != null)
{
dataPrepLinearReg lr = new dataPrepLinearReg();
lr.getLrModel(ln, BuildModel);
lrLst.Add(lr);
ln = sr.ReadLine();
if (IndependentFieldNames == null)
{
IndependentFieldNames = lr.IndependentFieldNames;
DependentFieldNames = lr.DependentFieldNames;
ClassFieldNames = lr.ClassFieldNames;
}
}
sr.Close();
mvr = lrLst.ToArray();
}
}
private void getLinearRegressions()
{
mvr = new dataPrepLinearReg[DependentFieldNames.Length];
for (int i = 0; i < DependentFieldNames.Length; i++)
{
mvr[i] = new dataPrepLinearReg(InTable, new string[] { DependentFieldNames[i] }, IndependentFieldNames, ClassFieldNames, intOrigin);
}
}
private void createLinearRegressionModel(string[] paramArr)
{
ITable table = getTable(paramArr[1]);
string[] dependentField = paramArr[2].Split(new char[]{','});
string[] independentFields = paramArr[3].Split(new char[]{','});
string[] categoricalFields = paramArr[4].Split(new char[]{','});
Statistics.dataPrepLinearReg dpLg = null;
if (paramArr.Length > 5)
{
bool z = true;
if (paramArr[5].ToLower() == "false") z = false;
dpLg = new Statistics.dataPrepLinearReg(table, dependentField, independentFields, categoricalFields, z);
}
else
{
dpLg = new Statistics.dataPrepLinearReg(table, dependentField, independentFields, categoricalFields);
}
dpLg.writeModel(paramArr[paramArr.Length - 1]);
}
public void getMlrModel(string modelPath, bool BuildModel = false)
{
using (System.IO.StreamReader sr = new System.IO.StreamReader(modelPath))
{
string mType = sr.ReadLine();
modelTypes m = (modelTypes)Enum.Parse(typeof(modelTypes), mType);
if (m != modelTypes.MvlRegression)
{
System.Windows.Forms.MessageBox.Show("Model file specified is not a Multivariate Linear Regression Model!!", "Error", System.Windows.Forms.MessageBoxButtons.OK, System.Windows.Forms.MessageBoxIcon.Error);
return;
}
string ln = sr.ReadLine();
List<dataPrepLinearReg> lrLst = new List<dataPrepLinearReg>();
while (ln != null)
{
dataPrepLinearReg lr = new dataPrepLinearReg();
lr.getLrModel(ln,BuildModel);
lrLst.Add(lr);
ln = sr.ReadLine();
if (IndependentFieldNames==null)
{
IndependentFieldNames = lr.IndependentFieldNames;
DependentFieldNames = lr.DependentFieldNames;
ClassFieldNames = lr.ClassFieldNames;
}
}
sr.Close();
mvr = lrLst.ToArray();
}
}
private void getLinearRegressions()
{
mvr = new dataPrepLinearReg[DependentFieldNames.Length];
for (int i = 0; i < DependentFieldNames.Length; i++)
{
mvr[i] = new dataPrepLinearReg(InTable, new string[] { DependentFieldNames[i] }, IndependentFieldNames, ClassFieldNames, intOrigin);
}
}
