package assoc_rules;

import java.io.File;

import java.io.FileWriter;

import java.time.LocalDateTime;

import weka.associations.Apriori;

import weka.associations.FPGrowth;

import weka.core.Instances;

import weka.core.converters.ConverterUtils.DataSource;

/**

 * This class implements FP growth algorithm to obtain association rule from clean, UMLS mapped and filtered FAERS data

 * @author zhengc

 *

 */

public class AssocFPGrowth{

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

        //load dataset

        String dataset = args[0];

        System.out.println("Algorithm starts: " + LocalDateTime.now());

        System.out.println();

        DataSource source = new DataSource(dataset);

        //get instances object 

        Instances data = source.getDataSet();

        int numAttr = data.numAttributes();

        int numIns =  data.numInstances();

        System.out.println("Number of attributes is " + numAttr);

        System.out.println("Number of instances is " + numIns);

        // lift-based algorithm

        String[] opts = new String[10];

        opts[0] = "-T"; opts[1] = "1";

        opts[2] = "-C"; opts[3] = "1";

        opts[4] = "-M"; opts[5] = "0.000002";

        opts[6] = "-N"; opts[7] ="200000";

        opts[8] = "-I"; opts[9] = "3";

        model.setOptions(opts);

        //build model

        model.buildAssociations(data);

        //print out and save the extracted rules to file

        String results = model.toString();

        System.out.println(results);

        FileWriter fw = new FileWriter(new File(resultfile));

        fw.write(results);

        fw.close();

        System.out.println("Algorithm ends: " + LocalDateTime.now());

    }

}