/* -------------------------------------------------------------------------- */
/*                                                                            */
/*     D E C I S S I O N   T R E E   2 - F I L E   A P P L I C A T I O N      */
/*                     (I N F O R M A T I O N   G A I N)                      */
/*                                                                            */
/*                                Frans Coenen                                */
/*                                                                            */
/*                            Tuesday 3 January 2012                          */
/*                    Updates: Tuesday 10 January 2012                        */
/*                                                                            */
/* -------------------------------------------------------------------------- */

// Dept Computer Science, University of Liverpool

//import lucsKDD_ARM.*;
import java.io.*;

// decision tree application class using information gain as 
// the "splitting criteria".

class DecTreeInfoGain_2file_App {

    // ------------------- FIELDS ------------------------

    // Mone

    // ---------------- CONSTRUCTORS ---------------------

    // None

    // ------------------ METHODS ------------------------

    /* MAIN */

    public static void main(String[] args) throws IOException {

		// Create instance of class decisionTree
        DecTreeInfoGain newDecisionTree = new DecTreeInfoGain(args);

		// Read training input file (method in AssocRuleMining class), and
		// test inputfile (method in AprioriTFPclass).
		newDecisionTree.inputDataSet();	
		newDecisionTree.inputTestDataSet();

        // Output opportunity
		//newDecisionTree.outputDataArray();
		//newDecisionTree.outputTestDataArray();
		
		// Process Data
		double time1 = (double) System.currentTimeMillis();
		newDecisionTree.startClassification2file();
		newDecisionTree.outputDuration(time1,
                                         (double) System.currentTimeMillis());

		// Output
		//newDecisionTree.outputNumClasses();
		//newDecisionTree.outputTestDataArray();
		//newDecisionTree.outputDataArray();
		//newDecisionTree.outputDecTree();
		//newDecisionTree.outputRulesWithDefault();
        }
    }