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ssdp's Introduction

Introduction

SSDP is an evolutionary algorithm for Discriminative Pattern (DP) mining that focuses on high dimensional data sets.

New version of SSDP (SSDP+):

https://github.com/tarcisiodpl/ssdp_plus https://ieeexplore.ieee.org/document/8477855

Reference:

Tarcísio Lucas, Túlio C.P.B. Silva, Renato Vimieiro, Teresa B. Ludermir, A new evolutionary algorithm for mining top-k discriminative patterns in high dimensional data, Applied Soft Computing, Volume 59, October 2017, Pages 487-499, ISSN 1568-4946, https://doi.org/10.1016/j.asoc.2017.05.048.

Description folders:

SSDP

Java implementation of SSDP. Class Main is a self explanatory way how to run the algorithm:

    //====================================================================
    //== CONFIGURATION ===================================================
    //====================================================================
    //CSV database path
    String caminho = "C:\\Users\\Tarcisio  Lucas\\Documents\\NetBeansProjects\\SSDP\\pastas\\bases\\"; 
    //String nomeBase = "audiology_pn.CSV";
    String nomeBase = "alon-pn-freq-2.CSV";
    String caminhoBase = caminho + nomeBase;
   
    D.SEPARADOR = ","; //separator database
    Const.random = new Random(Const.SEEDS[0]); //Seed - 30 options
    
    //Parameters of the algorithm
    int k = 10; //number of DPs
    //String tipoAvaliacao = Avaliador.TIPO_WRACC; //Fitness
    String tipoAvaliacao = Avaliador.TIPO_QG; //Fitness
    //String tipoAvaliacao = Avaliador.TIPO_SUB; //Fitness
    D.valorAlvo = "p"; //target value of dataset
    
    //====================================================================
    //= END ==============================================================
    //====================================================================
           
    D.CarregarArquivo(caminhoBase, D.TIPO_CSV); //Loading database         
    Pattern.numeroIndividuosGerados = 0; //Initializing count of generated individuals by SSDP
                        
    //Rodando SSDP
    long t0 = System.currentTimeMillis(); //Initial time
    Pattern[] p = SSDP_MxC_Auto_3x3.run(k, tipoAvaliacao); //run SSDP
    double tempo = (System.currentTimeMillis() - t0)/1000.0; //time
    
    //Informations about top-k DPs:  
    System.out.println("### Base:" + D.nomeBase); //database name
    System.out.println("Average " + tipoAvaliacao + ": " + Avaliador.avaliarMedia(p, k));
    System.out.println("Time(s): " + tempo);
    System.out.println("Average size: " + Avaliador.avaliarMediaDimensoes(p,k));        
    System.out.println("Coverage of all k DPs in relation to D+: " + Avaliador.coberturaPositivo(p, k)*100 + "%");
    System.out.println("Number of individuals generated: " + Pattern.numeroIndividuosGerados);
    System.out.println("\n### Top-k DPs:");
    Avaliador.imprimirRegras(p, k);

experiments:

Experiments results:

Confrontation between the 8 SSDP versions tested on 121 high-dimensional bases: BIO-126-8SSDP-Qg-Tabelao.csvs

Confrontation between SSDP, SD, Trivial and Random search 121 high-dimensional bases: BIO-126-SSDPauto3x3xSDxTrivialxRamdon3M-Qg-Tabelao-nomeClean.csv

Confrontation between SSDP and evolutionary approach on 20 traditional bases: UCI-20-SSDPxNMEEFxMESDIFxSDIGA-Tabelao.csv

data:

10 microarray databases following the format accepted by the Java implementation. Basically they are .csv files where the label is in the last column.

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