public void CreateMiningModel()
{
//connecting the server and database
Server myServer = new Server();
myServer.Connect("DataSource=localhost;Catalog=FoodMart");
Database myDatabase = myServer.Databases["FoodMart"];
Cube myCube = myDatabase.Cubes["FoodMart 2000"];
CubeDimension myDimension = myCube.Dimensions["Customer"];
Microsoft.AnalysisServices.MiningStructure myMiningStructure =
myDatabase.MiningStructures.Add("CustomerSegement", "CustomerSegement");
//Bind the mining structure to a cube.
myMiningStructure.Source = new CubeDimensionBinding(".",
myCube.ID, myDimension.ID);
// Create the key column.
CubeAttribute customerKey = myCube.Dimensions["Customer"].Attributes["Customer"];
ScalarMiningStructureColumn keyStructureColumn =
CreateMiningStructureColumn(customerKey, true);
myMiningStructure.Columns.Add(keyStructureColumn);
//Member Card attribute
CubeAttribute memberCard =
myCube.Dimensions["Customer"].Attributes["Member Card"];
ScalarMiningStructureColumn memberCardStructureColumn = CreateMiningStructureColumn(memberCard, false);
myMiningStructure.Columns.Add(memberCardStructureColumn);
//Total Children attribute
CubeAttribute totalChildren = myCube.Dimensions["Customer"].Attributes["Total Children"];
ScalarMiningStructureColumn totalChildrenStructureColumn = CreateMiningStructureColumn(totalChildren, false);
myMiningStructure.Columns.Add(totalChildrenStructureColumn);
//Store Sales measure ToDo: fix this!
//Microsoft.AnalysisServices.Measure storeSales = myCube.MeasureGroups[0].Measures["Store Sales"];
//ScalarMiningStructureColumn storeSalesStructureColumn = CreateMiningStructureColumn(storeSales, false);
//myMiningStructure.Columns.Add(storeSalesStructureColumn);
//Create a mining model from the mining structure. By default, all the
//structure columns are used. Nonkey columns are with usage input
Microsoft.AnalysisServices.MiningModel myMiningModel = myMiningStructure.CreateMiningModel(true, "CustomerSegment");
//Set the algorithm to be clustering.
myMiningModel.Algorithm = MiningModelAlgorithms.MicrosoftClustering;
//Process structure and model
try
{
myMiningStructure.Update(UpdateOptions.ExpandFull);
myMiningStructure.Process(ProcessType.ProcessFull);
}
catch (Microsoft.AnalysisServices.OperationException e)
{
string err = e.Message;
}
}
/*
* Create mining model
*/
private void CreateMiningModel(Microsoft.AnalysisServices.MiningStructure objStructure, string sName, string sAlgorithm,
List <string> lsAtrPredict, List <string> lsMeasurePredict, List <bool> lbPredictItems, int parOne, int parTwo)
{
Microsoft.AnalysisServices.MiningModel myMiningModel = objStructure.CreateMiningModel(true, sName);
/* Notes:
* Each mining column must have its' input and predict columns
* Input and key columns are added automatically when they are created in the mining structure
* Predict columns can be added in the mining model
* An input column can be also a predict column
*/
myMiningModel.Algorithm = sAlgorithm;
switch (sAlgorithm)
{
case MiningModelAlgorithms.MicrosoftClustering:
myMiningModel.AlgorithmParameters.Add("CLUSTERING_METHOD", parOne);
if (parTwo > 0)
{
myMiningModel.AlgorithmParameters.Add("CLUSTER_COUNT", parTwo);
}
break;
//case MiningModelAlgorithms.MicrosoftTimeSeries:
// myMiningModel.AlgorithmParameters.Add("PERIODICITY_HINT", "{12}"); // {12} represents the number of months for prediction
// break;
case MiningModelAlgorithms.MicrosoftNaiveBayes:
break;
case MiningModelAlgorithms.MicrosoftDecisionTrees:
myMiningModel.AlgorithmParameters.Add("SCORE_METHOD", parOne);
myMiningModel.AlgorithmParameters.Add("SPLIT_METHOD", parTwo);
break;
}
/***************** Predict columns *****************/
// add optional predict columns
if (lsAtrPredict.Count != 0)
{
// predict columns
for (int i = 0; i < lsAtrPredict.Count; i++)
{
Microsoft.AnalysisServices.MiningModelColumn modelColumn = myMiningModel.Columns.GetByName(lsAtrPredict[i]);
modelColumn.SourceColumnID = lsAtrPredict[i];
if (lbPredictItems[i] == true)
{
modelColumn.Usage = MiningModelColumnUsages.PredictOnly;
}
else
{
modelColumn.Usage = MiningModelColumnUsages.Predict;
}
}
}
myMiningModel.Update();
}
/*---------------------------------
* Description: Update Mining Model and process StockPredict DB with new MAX, MIN when MAX,MIN are changed by Technology Analysis (IdentifyTrend)
* ----------------------------------- */
public static bool UpdateMMbyAnalysis(string sStockCode)
{
Server svr = ConnectServer(str_Con_Svr);
Database db = svr.Databases.GetByName("StockPredict");
Microsoft.AnalysisServices.MiningStructure ms = db.MiningStructures.FindByName(sStockCode);
Microsoft.AnalysisServices.MiningModel mm = ms.MiningModels.FindByName(sStockCode);
mm.AlgorithmParameters.Remove("MAXIMUM_SERIES_VALUE");
mm.AlgorithmParameters.Remove("MINIMUM_SERIES_VALUE");
// Max, Min Time Series
mm.AlgorithmParameters.Add("MAXIMUM_SERIES_VALUE", MAXIMUM_SERIES_VALUE);
mm.AlgorithmParameters.Add("MINIMUM_SERIES_VALUE", MINIMUM_SERIES_VALUE);
mm.Update();
mm.Process(ProcessType.ProcessFull);
// Update parameters into StockForecastModel
try
{
SqlConnection conn = new SqlConnection(str_Con_SQL);
conn.Open();
SqlCommand cmdUpdate = conn.CreateCommand();
cmdUpdate.CommandText = "Update StockForecastModel Set MAXIMUM_SERIES_VALUE=" + MAXIMUM_SERIES_VALUE.ToString().Replace(',', '.')
+ ", MINIMUM_SERIES_VALUE=" + MINIMUM_SERIES_VALUE.ToString().Replace(',', '.')
+ " Where StockCode='" + sStockCode + "'";
cmdUpdate.ExecuteNonQuery();
cmdUpdate.Dispose();
conn.Close();
}
catch (Exception ex) { MessageBox.Show("Không thể cập nhật StockForecastModel!"); return(false); }
return(true);
}
// Mining sample model
private void CreateMarketBasketModel()
{
CubeAttribute basketAttribute;
CubeAttribute itemAttribute;
Server myServer = new Server();
myServer.Connect("DataSource=localhost;Catalog=FoodMart");
Database myDatabase = myServer.Databases["FoodMart"];
Cube myCube = myDatabase.Cubes["FoodMart 2000"];
CubeDimension myDimension = myCube.Dimensions["Customer"];
Microsoft.AnalysisServices.MiningStructure myMiningStructure =
myDatabase.MiningStructures.Add("MarketBasket", "MarketBasket");
myMiningStructure.Source = new CubeDimensionBinding(".", myCube.ID, myDimension.ID);
basketAttribute = myCube.Dimensions["Customer"].Attributes["Customer"];
itemAttribute = myCube.Dimensions["Product"].Attributes["Product"];
//basket structure column
ScalarMiningStructureColumn basket = CreateMiningStructureColumn(basketAttribute, true);
basket.Name = "Basket";
myMiningStructure.Columns.Add(basket);
//item structure column - nested table
ScalarMiningStructureColumn item =
CreateMiningStructureColumn(itemAttribute, true);
item.Name = "Item";
MeasureGroup measureGroup = myCube.MeasureGroups[0];
TableMiningStructureColumn purchases =
CreateMiningStructureColumn(measureGroup);
purchases.Name = "Purchases";
purchases.Columns.Add(item);
myMiningStructure.Columns.Add(purchases);
Microsoft.AnalysisServices.MiningModel myMiningModel = myMiningStructure.CreateMiningModel();
myMiningModel.Name = "MarketBasket";
myMiningModel.Columns["Purchases"].Usage = MiningModelColumnUsages.PredictOnly;
myMiningModel.Algorithm = MiningModelAlgorithms.MicrosoftAssociationRules;
}
/*---------------------------------
* Description: Create Mining Model
* ----------------------------------- */
public static void CreateMM(Microsoft.AnalysisServices.MiningStructure ms, string strStockCode, bool bMulti)
{
if (ms.MiningModels.ContainsName(strStockCode))
{
ms.MiningModels[strStockCode].Drop();
}
Microsoft.AnalysisServices.MiningModel mm = ms.CreateMiningModel(true, strStockCode);
mm.Algorithm = MiningModelAlgorithms.MicrosoftTimeSeries;
InitialParameters(strStockCode);
// 0.1:0.05 -> from 0 to (1-0.1)/0.05=18
mm.AlgorithmParameters.Add("COMPLEXITY_PENALTY", COMPLEXITY_PENALTY);
// {5,20,60}, 0:0.1 -> from 0 to (1-0.1)/0.05=18
mm.AlgorithmParameters.Add("PERIODICITY_HINT", "{5,20,60}");
mm.AlgorithmParameters.Add("AUTO_DETECT_PERIODICITY", AUTO_DETECT_PERIODICITY);
// Defeult: 1, 10
mm.AlgorithmParameters.Add("HISTORIC_MODEL_COUNT", HISTORIC_MODEL_COUNT);
mm.AlgorithmParameters.Add("HISTORIC_MODEL_GAP", HISTORIC_MODEL_GAP);
// Max, Min Time Series
mm.AlgorithmParameters.Add("MAXIMUM_SERIES_VALUE", MAXIMUM_SERIES_VALUE);
mm.AlgorithmParameters.Add("MINIMUM_SERIES_VALUE", MINIMUM_SERIES_VALUE);
mm.AllowDrillThrough = true;
mm.Columns["ID"].Usage = MiningModelColumnUsages.Key;
mm.Columns["ClosePrice"].Usage = MiningModelColumnUsages.Predict;
if (strStockCode.ToUpper() != "VNINDEX" && !bMulti)
{
mm.Columns["OpenPrice"].Usage = MiningModelColumnUsages.Input;
mm.Columns["HighPrice"].Usage = MiningModelColumnUsages.Input;
mm.Columns["LowPrice"].Usage = MiningModelColumnUsages.Input;
//mm.Columns["Volume"].Usage = MiningModelColumnUsages.Input;
}
mm.Update();
// Update parameters into StockForecastModel
UpdateForecastModel(strStockCode);
}
public void AddMiningStructure()
{
Server srv = new Server();
srv.Connect("DataSource=CLARITY-7HYGMQM\\ANA;Initial Catalog=Adventure Works DW 2008");
Database db = srv.Databases["Adventure Works DW 2008"];
Cube myCube = db.Cubes["Adventure Works"];
CubeDimension myDimension = myCube.Dimensions.GetByName("Customer");
Microsoft.AnalysisServices.MiningStructure myMiningStructure = db.MiningStructures.Add("TestMining", "TestMining");
myMiningStructure.Source = new CubeDimensionBinding(".", myCube.ID, myDimension.ID);
// get current mining models
// Demo code
foreach (Microsoft.AnalysisServices.MiningStructure ms in db.MiningStructures)
{
Console.WriteLine(ms.Name);
foreach (Microsoft.AnalysisServices.MiningModel mm in ms.MiningModels)
{
Console.WriteLine(mm.Name);
}
}
CubeAttribute basketAttribute;
CubeAttribute itemAttribute;
basketAttribute = myCube.Dimensions.GetByName("Customer").Attributes[0];
itemAttribute = myCube.Dimensions.GetByName("Product").Attributes[0];
//basket structure column
ScalarMiningStructureColumn basket = CreateMiningStructureColumn(basketAttribute, true);
basket.Name = "Basket";
myMiningStructure.Columns.Add(basket);
//item structure column - nested table
ScalarMiningStructureColumn item = CreateMiningStructureColumn(itemAttribute, true);
item.Name = "Item";
MeasureGroup measureGroup = myCube.MeasureGroups[0];
TableMiningStructureColumn purchases = CreateMiningStructureColumn(measureGroup);
purchases.Name = "Purchases";
purchases.Columns.Add(item);
myMiningStructure.Columns.Add(purchases);
Microsoft.AnalysisServices.MiningModel myMiningModel = myMiningStructure.CreateMiningModel();
myMiningModel.Name = "MarketBasket";
myMiningModel.Columns["Purchases"].Usage = MiningModelColumnUsages.PredictOnly;
myMiningModel.Algorithm = MiningModelAlgorithms.MicrosoftAssociationRules;
try
{
myMiningStructure.Update(UpdateOptions.ExpandFull);
myMiningStructure.Process(ProcessType.ProcessFull);
}
catch (Microsoft.AnalysisServices.OperationException e)
{
this.sResult = e.StackTrace;
Console.WriteLine(e.StackTrace);
}
}
/*
* Create mining structures and models for olap
*/
public string CreateCubeMiningStructure(string sStructName, string sAlgorithm, int sCubeName, string sDimensionName, string sKeyColumn,
List <string> lsInputColumns, List <string> lsPredictColumns, List <string> lsMeasureInput, List <string> lsMeasurePredict, List <bool> lbPredictItems,
int parOne, int parTwo)
{
try
{
// connect to cube
Server objServer = new Server();
objServer.Connect("DataSource=" + sServer + ";Initial Catalog=" + sCatalog);
Database objDb = objServer.Databases[sCatalog];
Cube objCube = objDb.Cubes[sCubeName];
DataSourceView myView = objDb.DataSourceViews[0];
// create mining structure
CubeDimension objDimension = objCube.Dimensions.GetByName(sDimensionName);
// drop the existing structures with the same name
Microsoft.AnalysisServices.MiningStructure currentMiningStruct = objDb.MiningStructures.FindByName(sStructName);
if (currentMiningStruct != null)
{
currentMiningStruct.Drop();
}
Microsoft.AnalysisServices.MiningStructure myMiningStructure = objDb.MiningStructures.Add(sStructName, sStructName);
myMiningStructure.Source = new CubeDimensionBinding(".", objCube.ID, objDimension.ID);
/***************** Key column *****************/
// key column
CubeAttribute objKey = objCube.Dimensions.GetByName(sDimensionName).Attributes[0];
ScalarMiningStructureColumn objKeyColumn = CreateMiningStructureColumn(objKey, true);
objKeyColumn.Name = sKeyColumn;
myMiningStructure.Columns.Add(objKeyColumn);
/***************** Other columns *****************/
// create mining columns
for (int i = 0; i < lsInputColumns.Count; i++)
{
// get attribute
CubeAttribute objAttribute = new CubeAttribute();
objAttribute = objCube.Dimensions.GetByName(sDimensionName).Attributes[0];
// create mining column
ScalarMiningStructureColumn objColumn = CreateMiningStructureColumn(objAttribute, false);
objColumn.Name = lsInputColumns[i];
myMiningStructure.Columns.Add(objColumn);
/***************** Measure column *****************/
// create mining columns for measures
for (int j = 0; j < lsMeasureInput.Count; j++)
{
MeasureGroup objMeasureGroup = objCube.MeasureGroups[lsMeasureInput[j]];
TableMiningStructureColumn objMeasure = CreateMiningStructureColumn(objMeasureGroup);
objMeasure.Name = lsMeasureInput[j];
objMeasure.Columns.Add(objColumn);
myMiningStructure.Columns.Add(objMeasure);
}
}
/***************** Columns for prediction - will be updated in model *****************/
// create mining columns
for (int i = 0; i < lsPredictColumns.Count; i++)
{
// get attribute
CubeAttribute objAttribute = new CubeAttribute();
objAttribute = objCube.Dimensions.GetByName(sDimensionName).Attributes[0];
// if value = false (input & predict) then skip
if (lbPredictItems[i] == false)
{
continue;
}
else
{
// create mining column
ScalarMiningStructureColumn objColumn = CreateMiningStructureColumn(objAttribute, false);
objColumn.Name = lsPredictColumns[i];
myMiningStructure.Columns.Add(objColumn);
}
}
// update
myMiningStructure.Update();
/***************** Mining model *****************/
// create mining models
CreateMiningModel(myMiningStructure, sStructName, sAlgorithm, lsPredictColumns, lsMeasurePredict, lbPredictItems, parOne, parTwo);
// process
myMiningStructure.Process();
return("Success");
}
catch (Exception e)
{
return(e.Message);
}
}
public static void ProcessUpdateMMTest(Server svr, string strStockCode, bool bCon)
{
Database db = svr.Databases.GetByName("StockPredict");
Microsoft.AnalysisServices.MiningStructure ms = db.MiningStructures.FindByName(strStockCode);
string strMsg, strCap;
MessageBoxButtons buttons = MessageBoxButtons.OK;
if (ms == null)
{
strMsg = "Cấu trúc dự báo cho cổ phiếu này không tồn tại!";
strCap = "Mining Structure";
// Displays the MessageBox.
MessageBox.Show(strMsg, strCap, buttons, MessageBoxIcon.Error);
return;
}
Microsoft.AnalysisServices.MiningModel mm = ms.MiningModels.FindByName(strStockCode);
if (mm == null)
{
strMsg = "Mô hình dự báo cho cổ phiếu này không tồn tại!";
strCap = "Mining Model";
// Displays the MessageBox.
MessageBox.Show(strMsg, strCap, buttons, MessageBoxIcon.Error);
return;
}
// Check exist table: CR
ADOMDLib.ExistExpandTable(strStockCode, "_CRT", bCon);
// Initial parameters
DefaultParam(strStockCode);
// Get ToDate from StockForecastModel
SqlConnection cn = new SqlConnection(str_Con_SQL);
cn.Open();
SqlCommand cmd = new SqlCommand();
cmd.Connection = cn;
cmd.CommandText = "SELECT ToDate FROM StockForecastModel WHERE StockCode='" + strStockCode + "'";
SqlDataReader rdr = cmd.ExecuteReader();
rdr.Read();
DateTime dtTo = rdr.GetDateTime(0);
rdr.Close();
cn.Close();
// Loop mining
while (AUTO_DETECT_PERIODICITY < 0.95)
{
while (COMPLEXITY_PENALTY < 0.95)
{
while (HISTORIC_MODEL_COUNT < 3)
{
while (HISTORIC_MODEL_GAP < 15)
{
if (!UpdateMMTest(mm, strStockCode, dtTo))
{
// Update parameters into StockForecastModel
UpdateForecastModel(strStockCode);
return;
}
HISTORIC_MODEL_GAP++;
}
HISTORIC_MODEL_GAP = i_Save_HMG;
HISTORIC_MODEL_COUNT++;
}
HISTORIC_MODEL_COUNT = 1;
COMPLEXITY_PENALTY += 0.05;
}
COMPLEXITY_PENALTY = 0.05;
AUTO_DETECT_PERIODICITY += 0.05;
}
// Get the best parameters
UpdateMMTest(mm, strStockCode, dtTo);
GetBestParamTest(strStockCode);
UpdateForecastModel(strStockCode);
}
public static void ProcessUpdateMM(Server svr, string strStockCode, bool bCon)
{
Database db = svr.Databases.GetByName("StockPredict");
Microsoft.AnalysisServices.MiningStructure ms = db.MiningStructures.FindByName(strStockCode);
string strMsg, strCap;
MessageBoxButtons buttons = MessageBoxButtons.OK;
if (ms == null)
{
strMsg = "Cấu trúc dự báo cho cổ phiếu này không tồn tại!";
strCap = "Mining Structure";
// Displays the MessageBox.
MessageBox.Show(strMsg, strCap, buttons, MessageBoxIcon.Error);
return;
}
Microsoft.AnalysisServices.MiningModel mm = ms.MiningModels.FindByName(strStockCode);
if (mm == null)
{
strMsg = "Mô hình dự báo cho cổ phiếu này không tồn tại!";
strCap = "Mining Model";
// Displays the MessageBox.
MessageBox.Show(strMsg, strCap, buttons, MessageBoxIcon.Error);
return;
}
// Check exist table: CR
ADOMDLib.ExistExpandTable(strStockCode, "_CR", bCon);
// Initial parameters and get count of IDs
int iCount_ID = InitialParameters(strStockCode);
// Loop mining
while (AUTO_DETECT_PERIODICITY < 0.95)
{
while (COMPLEXITY_PENALTY < 0.95)
{
while (HISTORIC_MODEL_COUNT < 3)
{
while (HISTORIC_MODEL_GAP < 15)
{
HISTORIC_MODEL_GAP++;
if (!UpdateMM(mm, strStockCode, false))
{
// back to previous
//HISTORIC_MODEL_GAP--;
//UpdateMM(mm, strStockCode, true);
// Update parameters into StockForecastModel
UpdateForecastModel(strStockCode);
return;
}
}
HISTORIC_MODEL_GAP = i_Save_HMG;
HISTORIC_MODEL_COUNT++;
}
HISTORIC_MODEL_COUNT = 1;
COMPLEXITY_PENALTY += 0.05;
}
COMPLEXITY_PENALTY = 0.05;
AUTO_DETECT_PERIODICITY += 0.05;
}
// Get the best parameters
// Get the best parameters
UpdateMM(mm, strStockCode, false);
GetBestParam(strStockCode);
UpdateForecastModel(strStockCode);
}
/*---------------------------------
* Description: Create Mining Structure
* ----------------------------------- */
public static Microsoft.AnalysisServices.MiningStructure CreateMS(Microsoft.AnalysisServices.Server svr, string strStockCode, bool bAll, DateTime dtFrom, DateTime dtTo, bool bMulti)
{
Database db = svr.Databases.GetByName("Stock");
CreateDataAccessObjects(db, strStockCode, bAll, dtFrom, dtTo, bMulti, true);
Microsoft.AnalysisServices.MiningStructure ms = db.MiningStructures.FindByName(strStockCode);
if (ms != null)
{
// string message = "Bạn muốn tạo mới mô hình dự báo cho cổ phiếu này?";
// string caption = "Recreate New Mining Model";
// MessageBoxButtons buttons = MessageBoxButtons.YesNo;
// DialogResult result;
// // Displays the MessageBox.
// result = MessageBox.Show(message, caption, buttons);
// if (result == DialogResult.Yes)
// {
// ms.Drop();
// }
// else
// {
// //CreateMM(ms, strStockCode);
// return ms;
// }
ms.Drop();
}
// Add new Mining Structure
ms = db.MiningStructures.Add(strStockCode, strStockCode);
ms.Source = new DataSourceViewBinding(strStockCode);
ms.CaseTableName = strStockCode;
ScalarMiningStructureColumn intID = new ScalarMiningStructureColumn("ID", "ID");
intID.Type = MiningStructureColumnTypes.Long;
intID.Content = MiningStructureColumnContents.KeyTime;
intID.IsKey = true;
// Add data binding to the column.
intID.KeyColumns.Add(strStockCode, "ID", OleDbType.Integer);
// Add the column to the MiningStructure
ms.Columns.Add(intID);
ScalarMiningStructureColumn dblClosePrice = new ScalarMiningStructureColumn("ClosePrice", "ClosePrice");
dblClosePrice.Type = MiningStructureColumnTypes.Double;
dblClosePrice.Content = MiningStructureColumnContents.Continuous;
dblClosePrice.KeyColumns.Add(strStockCode, "ClosePrice", OleDbType.Double);
ms.Columns.Add(dblClosePrice);
// Don't use Open,High,Low for VNIndex, Compressed Date, and Multi Step Forecast
if (strStockCode.ToUpper() != "VNINDEX" && strStockCode.Length < 11 && !bMulti)
{
ScalarMiningStructureColumn dblOpenPrice = new ScalarMiningStructureColumn("OpenPrice", "OpenPrice");
dblOpenPrice.Type = MiningStructureColumnTypes.Double;
dblOpenPrice.Content = MiningStructureColumnContents.Continuous;
dblOpenPrice.KeyColumns.Add(strStockCode, "OpenPrice", OleDbType.Double);
ms.Columns.Add(dblOpenPrice);
ScalarMiningStructureColumn dblHighPrice = new ScalarMiningStructureColumn("HighPrice", "HighPrice");
dblHighPrice.Type = MiningStructureColumnTypes.Double;
dblHighPrice.Content = MiningStructureColumnContents.Continuous;
dblHighPrice.KeyColumns.Add(strStockCode, "HighPrice", OleDbType.Double);
ms.Columns.Add(dblHighPrice);
ScalarMiningStructureColumn dblLowPrice = new ScalarMiningStructureColumn("LowPrice", "LowPrice");
dblLowPrice.Type = MiningStructureColumnTypes.Double;
dblLowPrice.Content = MiningStructureColumnContents.Continuous;
dblLowPrice.KeyColumns.Add(strStockCode, "LowPrice", OleDbType.Double);
ms.Columns.Add(dblLowPrice);
//ScalarMiningStructureColumn lngVolume = new ScalarMiningStructureColumn("Volume", "Volume");
//lngVolume.Type = MiningStructureColumnTypes.Long;
//lngVolume.Content = MiningStructureColumnContents.Continuous;
//lngVolume.KeyColumns.Add(strStockCode, "Volume", OleDbType.Double);
//ms.Columns.Add(lngVolume);
}
ms.Update();
CreateMM(ms, strStockCode, bMulti);
return(ms);
}
