datamining.cs

一个经典的apriori算法（c#实现）

		/// <returns>
		/// A System.Data.DataSet in-memory database containing the Market Based Analysis results in
		/// the TransactionsTable, ItemsetTable, SubsetTable, Rulestable.
		/// </returns>
		/// <remarks>
		/// See  <see cref="VISUAL_BASIC_DATA_MINING_NET.DataAccessLayer.GetTransactionsData"/>
		/// </remarks>
		public Data MarketBasedAnalysis(double supportCount, double minimumConfidence, string connectionString, string																			dataSource, CommandType dataSourceCommand)
		{

			Database database = new Database();

			ItemsetCandidate Item = new ItemsetCandidate();

			this.AP = new APriori.Apriori();

			this.AP.ProgressMonitorEvent += new ProgressMonitorEventHandler(this.OnProgressMonitoringCompletedEvent);
			

			this.dataBase = database.GetTransactionsData(connectionString, dataSource, dataSourceCommand);

			database.Transactions = this.dataBase;
			
			
			this.transactionsCount = this.dataBase.TransactionTable.Count;
						
						
			supportCount = ((supportCount / 100) * this.transactionsCount);

			minimumConfidence = (minimumConfidence / 100);
			
			
			string support = "SupportCount >= " + supportCount + " AND Level > 1";

			string sort = "SupportCount, Level";
			
			
			ItemsetCandidate uniqueItems = AP.CreateOneItemsets(database);


			AP.AprioriGenerator(uniqueItems,database,Convert.ToInt32(supportCount));


			ItemsetArrayList [] keys = database.GetItemset(support, sort);


			
			string msg = "Creating Frequent Subsets for Items";
			
			ProgressMonitorEventArgs e = new ProgressMonitorEventArgs(1,100,95,"DataMining.MarketBasedAnalysis(3)",msg );

			this.OnProgressMonitorEvent(e);

				
			for(int counter = 0; counter < keys.Length; counter++)
			{
				AP.CreateItemsetSubsets(0,keys[counter], null, database);
			}


			
			msg = "Completed C#.NET Data Mining Market Based Analysis";
			
			e = new ProgressMonitorEventArgs(1,100,100,"DataMining.MarketBasedAnalysis(3)",msg );

			this.OnProgressMonitorEvent(e);

			
			
			//Set the public properties of the class
			this.minimumSupportCount = supportCount;

			this.minimumConfidence = minimumConfidence;

			this.connectionString = connectionString;

			this.dataSource = dataSource;

			this.dataSourceCommand = dataSourceCommand;

			//return the database of transactions
			return this.dataBase;
			
		}

		
		/// <summary>
		/// Retrieves the results of a Market Based Analysis as an in-memory cache of data from an XML file.
		/// </summary>
		/// <param name="supportCount">
		/// The support count is the number of transactions containing a set of items.
		/// </param>
		/// <param name="minimumConfidence">
		/// The confidence of two sets of items A and B is the number of transactions supported by A and B
		/// divided by the number of transactions divided by A and vice versa. 
		/// <example>
		/// confidence[A->B) = (number of transactions containing both A and B) / (number of transactions 
		///																			containing only A)
		/// </example>
		/// </param>
		/// <param name="xmlFilePath">
		/// The path to an XML file containing transaction data.
		/// </param>
		/// <returns>
		/// A System.Data.DataSet in-memory database containing the Market Based Analysis results in
		/// the TransactionsTable, ItemsetTable, SubsetTable, Rulestable.
		/// </returns>
		/// <remarks>
		/// See  <see cref="VISUAL_BASIC_DATA_MINING_NET.DataAccessLayer.GetXMLData"/>
		/// </remarks>
		public Data MarketBasedAnalysis(double supportCount, double minimumConfidence, string xmlFilePath)
		{

			Database database = new Database();

			ItemsetCandidate Item = new ItemsetCandidate();


			this.AP = new APriori.Apriori();

			this.AP.ProgressMonitorEvent += new ProgressMonitorEventHandler(this.OnProgressMonitoringCompletedEvent);
			

			this.dataBase = database.GetXMLData(xmlFilePath);


			database.Transactions = this.dataBase;
			
			
			this.transactionsCount = this.dataBase.TransactionTable.Count;
						
						
			supportCount = ((supportCount / 100) * this.transactionsCount);

			minimumConfidence = (minimumConfidence / 100);
			
			
			string support = "SupportCount >= " + supportCount + " AND Level > 1";

			string sort = "SupportCount, Level";
			
			
			ItemsetCandidate uniqueItems = AP.CreateOneItemsets(database);


			AP.AprioriGenerator(uniqueItems,database,Convert.ToInt32(supportCount));


			ItemsetArrayList [] keys = database.GetItemset(support, sort);


			
			string msg = "Creating Frequent Subsets for Items";
			
			ProgressMonitorEventArgs e = new ProgressMonitorEventArgs(1,100,95,"DataMining.MarketBasedAnalysis(3)",msg );

			this.OnProgressMonitorEvent(e);

				
			for(int counter = 0; counter < keys.Length; counter++)
			{
				AP.CreateItemsetSubsets(0,keys[counter], null, database);
			}


			
			msg = "Completed C#.NET Data Mining Market Based Analysis";
			
			e = new ProgressMonitorEventArgs(1,100,100,"DataMining.MarketBasedAnalysis(3)",msg );

			this.OnProgressMonitorEvent(e);

			
			//Set the public properties of the class
			this.minimumSupportCount = supportCount;

			this.minimumConfidence = minimumConfidence;

			this.xmlFilePath = xmlFilePath;

			//return the database of transactions
			return this.dataBase;
			
		}


		public Data MarketBasedAnalysis(double supportCount, double minimumConfidence, Data transactionsData)
		{

			Database database = new Database();

			ItemsetCandidate Item = new ItemsetCandidate();


			this.AP = new APriori.Apriori();

			this.AP.ProgressMonitorEvent += new ProgressMonitorEventHandler(this.OnProgressMonitoringCompletedEvent);
			

			this.dataBase = transactionsData;


			database.Transactions = this.dataBase;
			
			
			this.transactionsCount = this.dataBase.TransactionTable.Count;
						
						
			supportCount = ((supportCount / 100) * this.transactionsCount);

			minimumConfidence = (minimumConfidence / 100);
			
			
			string support = "SupportCount >= " + supportCount + " AND Level > 1";

			string sort = "SupportCount, Level";
			
			
			ItemsetCandidate uniqueItems = AP.CreateOneItemsets(database);


			AP.AprioriGenerator(uniqueItems,database,Convert.ToInt32(supportCount));


			ItemsetArrayList [] keys = database.GetItemset(support, sort);



			string msg = "Creating Frequent Subsets for Items";
			
			ProgressMonitorEventArgs e = new ProgressMonitorEventArgs(1,100,95,"DataMining.MarketBasedAnalysis(3)",msg );

			this.OnProgressMonitorEvent(e);
	

			for(int counter = 0; counter < keys.Length; counter++)
			{
				AP.CreateItemsetSubsets(0,keys[counter], null, database);
			}

			
			msg = "Completed C#.NET Data Mining Market Based Analysis";
			
			e = new ProgressMonitorEventArgs(1,100,100,"DataMining.MarketBasedAnalysis(3)",msg );

			this.OnProgressMonitorEvent(e);
			

			
			//Set the public properties of the class
			this.minimumSupportCount = supportCount;

			this.minimumConfidence = minimumConfidence;

			//return the database of transactions
			return this.dataBase;
			
		}
		
		
		/// <summary>
		/// A DataView for viewing the results of the Market Based Analysis Data Mining results. 
		/// </summary>
		/// <returns>
		///A System.Data.DataView object for viewing the tables of the Market Based Analysis tables.
		/// </returns>
		public DataView ViewDataMiningAnalysis()
		{
			double minimumconfidence = ((this.minimumConfidence) * 100);

			string confidence = "Confidence >= " + minimumconfidence + "%";
 
			viewDataMiningAnalysis = new DataView(this.dataBase.Tables["ViewRulesTable"], confidence, "Confidence",														DataViewRowState.CurrentRows);			
			
			return viewDataMiningAnalysis;
		}
				
		
		/// <summary>
		/// A DataView for viewing the contents of any of the Market Based Analysis tables.
		/// </summary>
		/// <param name="tableName">
		/// The name of the table containing the results to be viewed with the DataView object.
		/// </param>
		/// <returns>
		/// A System.Data.DataView object for viewing the tables of the Market Based Analysis tables.
		/// </returns>
		public DataView ViewDataMiningAnalysis(string tableName)
		{
			viewDataMiningAnalysis = new DataView(this.dataBase.Tables[tableName]);

			return viewDataMiningAnalysis;
		}


		/// <summary>
		/// A DataView for viewing the contents of any of the Market Based Analysis tables.
		/// </summary>
		/// <param name="tableName">
		/// The name of the table containing the results to be viewed with the DataView object.
		/// </param>
		/// <param name="sortColumn">
		/// The name of the table column to use in sorting the data to be viewed.
		/// </param>
		/// <returns>
		/// A System.Data.DataView object for viewing the tables of the Market Based Analysis tables.
		/// </returns>
		public DataView ViewDataMiningAnalysis(string tableName, string sortColumn)
		{
			viewDataMiningAnalysis = new DataView(this.dataBase.Tables[tableName],"",sortColumn,DataViewRowState.CurrentRows);

			return viewDataMiningAnalysis;
		}


		/// <summary>
		/// A DataView for viewing the contents of any of the Market Based Analysis tables.
		/// </summary>
		/// <param name="tableName">
		/// The name of the table containing the results to be viewed with the DataView object.
		/// </param>
		/// <returns>
		/// A System.Data.DataView object for viewing the tables of the Market Based Analysis tables.
		/// </returns>
		public DataView ViewDataMiningAnalysis(string tableName, double minimumConfidence)
		{
			string confidence = "Confidence >= " + minimumConfidence;
 
			viewDataMiningAnalysis = new DataView(this.dataBase.Tables[tableName], confidence, "Confidence",														DataViewRowState.CurrentRows);			
			
			return viewDataMiningAnalysis;
		}


		

	}


}