Introduction

SSDP+ is an evolutionary approach for mining diverse and more informative subgroups focused on high dimensional data sets. SSDP+ is an extension of the SSDP model (https://github.com/tarcisiodpl/ssdp) to provide diversity in a way that explore the relation between subgroups order to generate a more informative set of patterns.

Link for SSDP+ paper:

https://ieeexplore.ieee.org/document/8477855

Video:

Rodando o SSDP+ (português): https://youtu.be/u175JvLD-38

Description folders:

SSDP+

Java implementation of SSDP+. SSDP+ was implemented as a Netbeans project. Thus, you have to:

1. download and install the Netbeans with Java (https://www.oracle.com/technetwork/pt/java/javase/downloads/jdk-netbeans-jsp-3413153-ptb.html)

2. download the SSDPplus of this repository and open in Neatbeans

3. Class SSDPplus contains a main method that is a self explanatory way how to run the algorithm:

    //*******************************************
    //Data set                    ***************
    //*******************************************
    String caminho = "C:\\Users\\Tarcisio  Lucas\\Documents\\NetBeansProjects\\SSDPplus\\pastas\\bases\\"; 
    //String nomeBase = "alon-clean50-pn-width-2.CSV";
    //String nomeBase = "ENEM2014_81_NOTA_10k.csv";
    String nomeBase = "matrixBinaria-Global-100-p.csv";
    String caminhoBase = caminho + nomeBase;
   
    //separator database (CSV files)
    D.SEPARADOR = ","; 
    //Seed
    Const.random = new Random(Const.SEEDS[0]); 
    //*******************************************
    //END Data set                    ***************
    //*******************************************
    
   
    //*******************************************
    //SSDP+ parameters            ***************
    //*******************************************
    //k: number of subgroups
    int k = 5; 
    //Evaluation metric
    String tipoAvaliacao = Avaliador.METRICA_AVALIACAO_WRACC; 
        //String tipoAvaliacao = Avaliador.METRICA_AVALIACAO_QG;
    //ks: cache size
    Pattern.maxSimulares = 2; 
    //min_similarity
    double similaridade = 0.10;
    //Similarity function
    Pattern.medidaSimilaridade = Const.SIMILARIDADE_JACCARD; //similarity function (default JACCARD)
    //Target (atributevalue)
    String target = "p";
    
    //*******************************************
    //END SSDP+ parameters            ***************
    //*******************************************
    
    //It is not about the SSDP+
    Pattern.ITENS_OPERATOR = Const.PATTERN_AND;
    
    //max time simulation in second (-1 for infinity)
    double maxTimeSecond =  -1;      
    
    System.out.println("Loading data set...");
    D.CarregarArquivo(caminhoBase, D.TIPO_CSV); //Loading data set        
    D.GerarDpDn(target);
    //"6,80,104,116,134,145,151,153,156,256"; //target value
    //D.valorAlvo = "I-III";
    //D.valorAlvo = "IV-VII";
    
    
    
    //*******************************************
    //FILTER BY ATTRIBUTE, VALUES AND ITEMS *****
    //*******************************************
    //Filter by attribute
    //String[] filtrarAtributos = {"C009"};
    String[] filtrarAtributos = null;
    //Filter by values
    String[] filtrarValores = null;
    //String[] filtrarValores = {"", "NA"};
    //Filter by items
    String[][] filtrarAtributosValores = null;
    //String[][] filtrarAtributosValores = new String[2][2];
    //filtrarAtributosValores[0][0] = "D001";
    //filtrarAtributosValores[0][1] = "2";
    //filtrarAtributosValores[1][0] = "E01002";
    //filtrarAtributosValores[1][1] = "8";
    //*******************************************
    //EDN FILTER BY ATTRIBUTE, VALUES AND ITEMS *****
    //*******************************************
   

experiments:

This folder contains the results of the experiments

data sets:

This folder contains part of the databases used in the experiments