/***********************************************************************
This file is part of KEEL-software, the Data Mining tool for regression,
classification, clustering, pattern mining and so on.
Copyright (C) 2004-2010
F. Herrera (herrera@decsai.ugr.es)
L. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (alberto.fernandez@ujaen.es)
J. Luengo (julianlm@decsai.ugr.es)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see http://www.gnu.org/licenses/
**********************************************************************/
/**
* <p>
* @author Written by Albert Orriols (La Salle, Ram�n Llull University - Barcelona) 28/03/2004
* @author Modified by Xavi Sol� (La Salle, Ram�n Llull University - Barcelona) 03/12/2008
* @version 1.1
* @since JDK1.2
* </p>
*/
/* Generated By:JavaCC: Do not edit this line. ParserConstants.java */
package keel.Algorithms.Genetic_Rule_Learning.XCS.KeelParser;
public interface ParserConstants {
int EOF = 0;
int COMENT = 6;
int COM2 = 7;
int PROBLEM = 8;
int CLASSIFIER = 9;
int PARAMETERS = 10;
int INIT = 11;
int GA = 12;
int REPRESENTATION = 13;
int STATISTICS = 14;
int REDUCTION = 15;
int BEGIN = 16;
int END = 17;
int XCSI = 18;
int TEST = 19;
int ALGORITHM = 20;
int INPUTDATA = 21;
int OUTPUTDATA = 22;
int TYPEOFPROBLEM = 23;
int NUMBEROFEXPLORES = 24;
int SEED = 25;
int EXPLORESBETWEENEXPLOITS = 26;
int XCSRUN = 27;
int TRAINFILE = 28;
int POPULATIONFILE = 29;
int PROBLEMTYPE = 30;
int RUNTYPE = 31;
int POPSIZE = 32;
int ALPHA = 33;
int BETA = 34;
int GAMMA = 35;
int DELTA = 36;
int NU = 37;
int THETA_MNA = 38;
int THETA_DEL = 39;
int THETA_SUB = 40;
int EPSILON_0 = 41;
int DOASSUBSUMPTION = 42;
int PREDICTIONERRORREDUCTION = 43;
int FITREDUCTION = 44;
int INITIALPREDICITON = 45;
int INITIALFITNESS = 46;
int INITIALPERROR = 47;
int PX = 48;
int PM = 49;
int THETA_GA = 50;
int DOGASUBSUMPTION = 51;
int TOURNAMENTSIZE = 52;
int TYPEOFMUTATION = 53;
int TYPEOFSELECTION = 54;
int TYPEOFCROSSOVER = 55;
int PERMITWITHINCROSSOVER = 56;
int SELECTIONTYPE = 57;
int CROSSOVERTYPE = 58;
int MUTATIONTYPE = 59;
int PDONTCARE = 60;
int CLLENGTH = 61;
int R_0 = 62;
int L_0 = 63;
int M_0 = 64;
int XCSI_L0 = 65;
int XCSI_M0 = 66;
int XCSI_R0 = 67;
int INTEGER = 68;
int SPECIFY = 69;
int DOSPECIFY = 70;
int PSPECIFY = 71;
int NSPECIFY = 72;
int DOSTATISTICS = 73;
int STATISTICFILEOUTNAME = 74;
int STATISTICWINDOWSIZE = 75;
int GETOPTIMALPOPULATION = 76;
int OPTIMALPOPULATIONFILE = 77;
int REALDRAWNPRECISION = 78;
int DOTEST = 79;
int TESTWINDOW = 80;
int SEQUENTIALTEST = 81;
int TESTFILE = 82;
int NUMBEROFTESTEXAMPLES = 83;
int DOREDUCTION = 84;
int TYPEOFREDUCTION = 85;
int INITREDUCTIONITERATION = 86;
int REDUCTWINDOW = 87;
int REDUCTEDRULESFILE = 88;
int THETA_REDUCT = 89;
int EPSILON_REDUCT = 90;
int P_REDUCT = 91;
int REDUCTIONTYPE = 92;
int EQUALS = 93;
int PCOMA = 94;
int COBERT = 95;
int CTANCAT = 96;
int COLON = 97;
int INT_CONST = 98;
int BOOLEAN_CONST = 99;
int CAR_CONST = 100;
int REAL_CONST = 101;
int CAD_CONST = 102;
int IDENT = 103;
int LLETRA = 104;
int DIGIT = 105;
int ERR_LEX = 106;
int DEFAULT = 0;
String[] tokenImage = {
"<EOF>",
"\" \"",
"\"\\t\"",
"\"\\b\"",
"\"\\n\"",
"\"\\r\"",
"<COMENT>",
"<COM2>",
"\"problem\"",
"\"classifier\"",
"\"parameters\"",
"\"init\"",
"\"GA\"",
"\"representation\"",
"\"statistics\"",
"\"reduction\"",
"\"begin\"",
"\"end\"",
"\"XCSI\"",
"\"test\"",
"\"algorithm\"",
"\"inputData\"",
"\"outputData\"",
"\"typeOfProblem\"",
"\"numberOfExplores\"",
"\"seed\"",
"\"exploresBetweenExploits\"",
"\"XCSRun\"",
"\"trainFile\"",
"\"populationFile\"",
"<PROBLEMTYPE>",
"<RUNTYPE>",
"\"popsize\"",
"\"alpha\"",
"\"beta\"",
"\"gamma\"",
"\"delta\"",
"\"nu\"",
"\"theta_mna\"",
"\"theta_del\"",
"\"theta_sub\"",
"\"epsilon_0\"",
"\"doASSubsumption\"",
"\"predictionErrorReduction\"",
"\"fitReduction\"",
"\"initialPrediction\"",
"\"initialFitness\"",
"\"initialPredictionError\"",
"\"px\"",
"\"pm\"",
"\"theta_ga\"",
"\"doGASubsumption\"",
"\"tournamentSize\"",
"\"typeOfMutation\"",
"\"typeOfSelection\"",
"\"typeOfCrossover\"",
"\"permitWithinCrossover\"",
"<SELECTIONTYPE>",
"<CROSSOVERTYPE>",
"<MUTATIONTYPE>",
"\"pdontcare\"",
"\"clLength\"",
"\"r_0\"",
"\"l_0\"",
"\"m_0\"",
"\"XCSI_l0\"",
"\"XCSI_m0\"",
"\"XCSI_r0\"",
"\"integer\"",
"\"specify\"",
"\"dospecify\"",
"\"pspecify\"",
"\"nspecify\"",
"\"doStatistics\"",
"\"statisticFileOutName\"",
"\"statisticWindowSize\"",
"\"getOptimalPopulation\"",
"\"optimalPopulationFile\"",
"\"realDrawnPrecision\"",
"\"doTest\"",
"\"testWindow\"",
"\"sequentialTest\"",
"\"testFile\"",
"\"numberOfTestExamples\"",
"\"doReduction\"",
"\"typeOfReduction\"",
"\"initReductionIteration\"",
"\"reductWindow\"",
"\"reductedRulesFile\"",
"\"theta_reduct\"",
"\"epsilon_reduct\"",
"\"Preduct\"",
"<REDUCTIONTYPE>",
"\"=\"",
"\";\"",
"\"[\"",
"\"]\"",
"\",\"",
"<INT_CONST>",
"<BOOLEAN_CONST>",
"<CAR_CONST>",
"<REAL_CONST>",
"<CAD_CONST>",
"<IDENT>",
"<LLETRA>",
"<DIGIT>",
"<ERR_LEX>",
};
}