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SSDP+ is an evolutionary approach for mining diverse and more informative subgroups focused on high dimensional data sets.

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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

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