- Timestamp:
- 07/05/16 09:41:17 (8 years ago)
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trunk/CrossPareConfigurationBuilder/src/de/ugoe/cs/crosspare/ConfigurationBuilder.java
r80 r133 7 7 8 8 public class ConfigurationBuilder { 9 10 private static enum Dataset {MDP, JURECZKO };9 10 private static enum Dataset {MDP, JURECZKO, FILTERJURECZKO, AEEEM, RELINK, NETGENE, SELECTEDJURECZKO}; 11 11 12 12 private static final String storageFolder = "config/"; … … 14 14 public static void main(String[] args) { 15 15 for( Dataset dataset : Dataset.values() ) { 16 writeFile("Koshgoftaar2008", dataset); 17 writeFile("Watanabe2008", dataset); 18 writeFile("Turhan2009", dataset); 19 writeFile("CamargoCruz2009", dataset); 20 // TODO Liu 2010 21 writeFile("Menzies2011", dataset); 22 writeFile("Ma2012", dataset); 23 writeFile("Peters2012", dataset); 24 writeFile("Uchigaki2012", dataset); 25 writeFile("Canfora2013", dataset); 26 writeFile("Peters2013", dataset); 27 writeFile("Herbold2013", dataset); 28 writeFile("ZHe2013", dataset); 29 writeFile("Nam2013", dataset); 30 writeFile("Panichella2014", dataset); 31 // TODO F.Zhang 2014 32 // TODO Mizuno 2014: data not public 33 writeFile("Ryu2014", dataset); 34 writeFile("PHe2015", dataset); 35 // TODO Peters 2015 (LACE2) 36 writeFile("Kawata2015", dataset); 37 writeFile("YZhang2015", dataset); 38 writeFile("Amasaki2015", dataset); 39 writeFile("Ryu2015b", dataset); 40 // TODO Cao 2015 implementation details missing 41 writeFile("Nam2015b", dataset); 16 // baselines 17 writeFile("ALL", dataset); 18 writeFile("CV", dataset); 19 writeFile("Random", dataset); 20 writeFile("Trivial", dataset); 21 // publications 22 writeFile("Koshgoftaar08", dataset); 23 writeFile("Watanabe08", dataset); 24 writeFile("Turhan09", dataset); 25 writeFile("Zimmermann09", dataset); 26 writeFile("CamargoCruz09", dataset); 27 writeFile("Liu10", dataset); 28 writeFile("Menzies11", dataset); 29 writeFile("Ma12", dataset); 30 writeFile("Peters12", dataset); 31 writeFile("Uchigaki12", dataset); 32 writeFile("Canfora13", dataset); 33 writeFile("Peters13", dataset); 34 writeFile("Herbold13", dataset); 35 writeFile("ZHe13", dataset); 36 writeFile("Nam13", dataset); 37 writeFile("Panichella14", dataset); 38 writeFile("Ryu14", dataset); 39 writeFile("PHe15", dataset); 40 writeFile("Peters15", dataset); 41 writeFile("Kawata15", dataset); 42 writeFile("YZhang15", dataset); 43 writeFile("Amasaki15", dataset); 44 writeFile("Ryu15", dataset); 45 writeFile("Nam15", dataset); 42 46 } 43 47 } … … 52 56 } 53 57 catch (IOException | IllegalAccessException | IllegalArgumentException | InvocationTargetException | NoSuchMethodException | SecurityException e) { 54 // TODO Auto-generated catch block55 58 e.printStackTrace(); 56 59 } … … 68 71 69 72 public static void trainers(StringBuilder configFile) { 70 configFile.append(" <trainer name=\"WekaTraining\" param=\"RandomForest weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5\" />\n"); 71 configFile.append(" <trainer name=\"WekaTraining\" param=\"C4.5-DTree weka.classifiers.trees.J48 -CVPARAM C 0.1 0.3 5\" />\n"); 72 configFile.append(" <trainer name=\"WekaTraining\" param=\"Logistic weka.classifiers.functions.Logistic\" />\n"); 73 configFile.append(" <trainer name=\"WekaTraining\" param=\"RBFNetwork weka.classifiers.functions.RBFNetwork -CVPARAM W 0.1 10.0 3.0 L 2.0 18.0 3.0\" />\n"); 74 configFile.append(" <trainer name=\"WekaTraining\" param=\"SMORBF weka.classifiers.functions.SMO -K weka.classifiers.functions.supportVector.RBFKernel\" />\n"); 73 configFile.append(" <trainer name=\"WekaTraining\" param=\"NB weka.classifiers.bayes.NaiveBayes\" />\n"); 74 configFile.append(" <trainer name=\"WekaTraining\" param=\"RF weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5\" />\n"); 75 configFile.append(" <trainer name=\"WekaTraining\" param=\"DT weka.classifiers.trees.J48 -CVPARAM C 0.1 0.3 5\" />\n"); 76 configFile.append(" <trainer name=\"WekaTraining\" param=\"LR weka.classifiers.functions.Logistic\" />\n"); 77 configFile.append(" <trainer name=\"WekaTraining\" param=\"NET weka.classifiers.functions.RBFNetwork -CVPARAM W 0.1 10.0 3.0 L 2.0 18.0 3.0\" />\n"); 78 configFile.append(" <trainer name=\"WekaTraining\" param=\"SVM weka.classifiers.functions.SMO -K weka.classifiers.functions.supportVector.RBFKernel\" />\n"); 75 79 } 76 80 77 81 public static void trainersBagging(StringBuilder configFile) { 78 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"BaggingRandomForest weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5\" />\n"); 79 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"BaggingC4.5-DTree weka.classifiers.trees.J48 -CVPARAM C 0.1 0.3 5\" />\n"); 80 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"BaggingLogistic weka.classifiers.functions.Logistic\" />\n"); 81 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"BaggingRBFNetwork weka.classifiers.functions.RBFNetwork -CVPARAM W 0.1 10.0 3.0 L 2.0 18.0 3.0\" />\n"); 82 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"BaggingSMORBF weka.classifiers.functions.SMO -K weka.classifiers.functions.supportVector.RBFKernel\" />\n"); 82 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"NB weka.classifiers.bayes.NaiveBayes\" />\n"); 83 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"RF weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5\" />\n"); 84 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"DT weka.classifiers.trees.J48 -CVPARAM C 0.1 0.3 5\" />\n"); 85 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"LR weka.classifiers.functions.Logistic\" />\n"); 86 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"NET weka.classifiers.functions.RBFNetwork -CVPARAM W 0.1 10.0 3.0 L 2.0 18.0 3.0\" />\n"); 87 configFile.append(" <setwisetrainer name=\"WekaBaggingTraining\" param=\"SVM weka.classifiers.functions.SMO -K weka.classifiers.functions.supportVector.RBFKernel\" />\n"); 83 88 } 84 89 85 90 public static void trainersLocalWhere(StringBuilder configFile) { 86 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"LocalRandomForest weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5\" />\n"); 87 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"LocalC4.5-DTree weka.classifiers.trees.J48 -CVPARAM C 0.1 0.3 5\" />\n"); 88 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"LocalLogistic weka.classifiers.functions.Logistic\" />\n"); 89 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"LocalRBFNetwork weka.classifiers.functions.RBFNetwork -CVPARAM W 0.1 10.0 3.0 L 2.0 18.0 3.0\" />\n"); 90 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"LocalSMORBF weka.classifiers.functions.SMO -K weka.classifiers.functions.supportVector.RBFKernel\" />\n"); 91 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"NB weka.classifiers.bayes.NaiveBayes\" />\n"); 92 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"RF weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5\" />\n"); 93 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"DT weka.classifiers.trees.J48 -CVPARAM C 0.1 0.3 5\" />\n"); 94 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"LR weka.classifiers.functions.Logistic\" />\n"); 95 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"NET weka.classifiers.functions.RBFNetwork -CVPARAM W 0.1 10.0 3.0 L 2.0 18.0 3.0\" />\n"); 96 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"SVM weka.classifiers.functions.SMO -K weka.classifiers.functions.supportVector.RBFKernel\" />\n"); 97 configFile.append(" <trainer name=\"WekaLocalFQTraining\" param=\"WHICH de.ugoe.cs.cpdp.wekaclassifier.WHICH\" />\n"); 91 98 } 92 99 93 100 public static void trainersLASER(StringBuilder configFile) { 94 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"LASERRandomForest weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5\" />\n"); 95 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"LASERC4.5-DTree weka.classifiers.trees.J48 -CVPARAM C 0.1 0.3 5\" />\n"); 96 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"LASERLogistic weka.classifiers.functions.Logistic\" />\n"); 97 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"LASERRBFNetwork weka.classifiers.functions.RBFNetwork -CVPARAM W 0.1 10.0 3.0 L 2.0 18.0 3.0\" />\n"); 98 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"LASERSMORBF weka.classifiers.functions.SMO -K weka.classifiers.functions.supportVector.RBFKernel\" />\n"); 101 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"NB weka.classifiers.bayes.NaiveBayes\" />\n"); 102 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"RF weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5\" />\n"); 103 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"DT weka.classifiers.trees.J48 -CVPARAM C 0.1 0.3 5\" />\n"); 104 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"LR weka.classifiers.functions.Logistic\" />\n"); 105 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"NET weka.classifiers.functions.RBFNetwork -CVPARAM W 0.1 10.0 3.0 L 2.0 18.0 3.0\" />\n"); 106 configFile.append(" <trainer name=\"WekaLASERTraining\" param=\"SVM weka.classifiers.functions.SMO -K weka.classifiers.functions.supportVector.RBFKernel\" />\n"); 99 107 } 100 108 … … 104 112 case MDP: 105 113 configFile.append(" <loader name=\"NasaARFFFolderLoader\" datalocation=\"benchmark/data/MDP\" relative=\"false\"/>\n"); 106 configFile.append(" <resultspath path=\"benchmark/results-csv\"/>\n");107 114 break; 108 115 case JURECZKO: 109 116 configFile.append(" <loader name=\"CSVFolderLoader\" datalocation=\"benchmark/data/JURECZKO\" relative=\"false\"/>\n"); 110 configFile.append(" <resultspath path=\"benchmark/results-csv\"/>\n"); 117 break; 118 case FILTERJURECZKO: 119 configFile.append(" <loader name=\"CSVFolderLoader\" datalocation=\"benchmark/data/JURECZKO\" relative=\"false\"/>\n"); 120 configFile.append(" <versionfilter name=\"MinInstanceNumberFilter\" param=\"100\" />\n"); 121 configFile.append(" <versionfilter name=\"UnbalancedFilter\" param=\"0.05\" />\n"); 122 break; 123 case AEEEM: 124 configFile.append(" <loader name=\"ARFFFolderLoader\" datalocation=\"benchmark/data/AEEEM\" relative=\"false\"/>\n"); 125 break; 126 case RELINK: 127 configFile.append(" <loader name=\"RelinkFolderLoader\" datalocation=\"benchmark/data/RELINK\" relative=\"false\"/>\n"); 128 break; 129 case NETGENE: 130 configFile.append(" <loader name=\"NetgeneFolderLoader\" datalocation=\"benchmark/data/NETGENE\" relative=\"false\"/>\n"); 131 break; 132 case SELECTEDJURECZKO: 133 configFile.append(" <loader name=\"CSVFolderLoader\" datalocation=\"benchmark/data/SELECTEDJURECZKO\" relative=\"false\"/>\n"); 111 134 break; 112 135 default: 113 136 throw new InvalidParameterException("Unknown data set: " + dataset.toString()); 114 137 } 115 } 116 117 public static String Koshgoftaar2008(Dataset dataset) { 138 configFile.append(" <versionfilter name=\"MinClassNumberFilter\" param=\"5\" />\n"); 139 configFile.append(" <resultspath path=\"benchmark/results-csv\"/>\n"); 140 } 141 142 public static String ALL(Dataset dataset) { 143 StringBuilder configFile = new StringBuilder(); 144 preamble(configFile); 145 dataset(configFile, dataset); 146 trainers(configFile); 147 148 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 149 150 postamble(configFile); 151 return configFile.toString(); 152 } 153 154 public static String CV(Dataset dataset) { 155 StringBuilder configFile = new StringBuilder(); 156 preamble(configFile); 157 dataset(configFile, dataset); 158 trainers(configFile); 159 160 configFile.append(" <eval name=\"CVWekaEvaluation\" param=\"\" />\n"); 161 162 postamble(configFile); 163 return configFile.toString(); 164 } 165 166 public static String Random(Dataset dataset) { 167 StringBuilder configFile = new StringBuilder(); 168 preamble(configFile); 169 dataset(configFile, dataset); 170 171 configFile.append(" <trainer name=\"WekaTraining\" param=\"RANDOM de.ugoe.cs.cpdp.wekaclassifier.RandomClass\" />\n"); 172 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 173 configFile.append(" <repetitions number=\"10\" />\n"); 174 175 postamble(configFile); 176 return configFile.toString(); 177 } 178 179 public static String Trivial(Dataset dataset) { 180 StringBuilder configFile = new StringBuilder(); 181 preamble(configFile); 182 dataset(configFile, dataset); 183 184 configFile.append(" <trainer name=\"WekaTraining\" param=\"FIX de.ugoe.cs.cpdp.wekaclassifier.FixClass -C 1\" />\n"); 185 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 186 187 postamble(configFile); 188 return configFile.toString(); 189 } 190 191 public static String Koshgoftaar08(Dataset dataset) { 118 192 StringBuilder configFile = new StringBuilder(); 119 193 preamble(configFile); … … 127 201 } 128 202 129 public static String Watanabe 2008(Dataset dataset) {203 public static String Watanabe08(Dataset dataset) { 130 204 StringBuilder configFile = new StringBuilder(); 131 205 preamble(configFile); … … 140 214 } 141 215 142 public static String Turhan 2009(Dataset dataset) {216 public static String Turhan09(Dataset dataset) { 143 217 StringBuilder configFile = new StringBuilder(); 144 218 preamble(configFile); … … 154 228 } 155 229 156 public static String CamargoCruz2009(Dataset dataset) { 230 public static String Zimmermann09(Dataset dataset) { 231 StringBuilder configFile = new StringBuilder(); 232 preamble(configFile); 233 dataset(configFile, dataset); 234 trainers(configFile); 235 236 configFile.append(" <setwiseselector name=\"DecisionTreeSelection\" param=\"max median stddev\" />\n"); 237 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 238 239 postamble(configFile); 240 return configFile.toString(); 241 } 242 243 public static String CamargoCruz09(Dataset dataset) { 157 244 StringBuilder configFile = new StringBuilder(); 158 245 preamble(configFile); … … 168 255 } 169 256 170 // TODO Liu 2010 171 172 public static String Menzies2011(Dataset dataset) { 257 public static String Liu10(Dataset dataset) { 258 StringBuilder configFile = new StringBuilder(); 259 preamble(configFile); 260 dataset(configFile, dataset); 261 262 configFile.append(" <setwisetrainer name=\"GPTraining\" param=\"numberRuns:1,errorType2Weight:15\" />"); 263 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 264 configFile.append(" <repetitions number=\"10\" />\n"); 265 266 postamble(configFile); 267 return configFile.toString(); 268 } 269 270 public static String Menzies11(Dataset dataset) { 173 271 StringBuilder configFile = new StringBuilder(); 174 272 preamble(configFile); … … 177 275 trainersLocalWhere(configFile); 178 276 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 179 180 postamble(configFile); 181 return configFile.toString(); 182 } 183 184 public static String Ma2012(Dataset dataset) { 277 configFile.append(" <repetitions number=\"10\" />\n"); 278 279 postamble(configFile); 280 return configFile.toString(); 281 } 282 283 public static String Ma12(Dataset dataset) { 185 284 StringBuilder configFile = new StringBuilder(); 186 285 preamble(configFile); … … 195 294 } 196 295 197 public static String Peters 2012(Dataset dataset) {296 public static String Peters12(Dataset dataset) { 198 297 StringBuilder configFile = new StringBuilder(); 199 298 preamble(configFile); … … 203 302 configFile.append(" <preprocessor name=\"MORPH\" param=\"\" />\n"); 204 303 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 205 206 postamble(configFile); 207 return configFile.toString(); 208 } 209 210 public static String Uchigaki2012(Dataset dataset) { 304 configFile.append(" <repetitions number=\"10\" />\n"); 305 306 postamble(configFile); 307 return configFile.toString(); 308 } 309 310 public static String Uchigaki12(Dataset dataset) { 211 311 StringBuilder configFile = new StringBuilder(); 212 312 preamble(configFile); … … 214 314 215 315 configFile.append(" <preprocessor name=\"ZScoreNormalization\" param=\"\" />\n"); 216 configFile.append(" <trainer name=\"WekaTraining\" param=\"L ogisticEnsemblede.ugoe.cs.cpdp.wekaclassifier.LogisticEnsemble\" />\n");217 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 218 219 postamble(configFile); 220 return configFile.toString(); 221 } 222 223 public static String Canfora 2013(Dataset dataset) {316 configFile.append(" <trainer name=\"WekaTraining\" param=\"LE de.ugoe.cs.cpdp.wekaclassifier.LogisticEnsemble\" />\n"); 317 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 318 319 postamble(configFile); 320 return configFile.toString(); 321 } 322 323 public static String Canfora13(Dataset dataset) { 224 324 StringBuilder configFile = new StringBuilder(); 225 325 preamble(configFile); … … 229 329 configFile.append(" <trainer name=\"WekaTraining\" param=\"MODEP de.ugoe.cs.cpdp.wekaclassifier.MODEPClassifier -R 0.7\" />\n"); 230 330 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 231 232 postamble(configFile); 233 return configFile.toString(); 234 } 235 236 public static String Peters2013(Dataset dataset) { 331 configFile.append(" <repetitions number=\"10\" />\n"); 332 333 postamble(configFile); 334 return configFile.toString(); 335 } 336 337 public static String Peters13(Dataset dataset) { 237 338 StringBuilder configFile = new StringBuilder(); 238 339 preamble(configFile); … … 241 342 242 343 configFile.append(" <preprocessor name=\"MORPH\" param=\"\" />\n"); 243 configFile.append(" <pointwiseselector name=\"CLIFF\" param=\"0.10\" />"); 244 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 245 246 postamble(configFile); 247 return configFile.toString(); 248 } 249 250 public static String Herbold2013(Dataset dataset) { 251 StringBuilder configFile = new StringBuilder(); 252 preamble(configFile); 253 dataset(configFile, dataset); 254 trainers(configFile); 344 configFile.append(" <pointwiseselector name=\"CLIFF\" param=\"0.40\" />"); 345 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 346 configFile.append(" <repetitions number=\"10\" />\n"); 347 348 postamble(configFile); 349 return configFile.toString(); 350 } 351 352 public static String Herbold13(Dataset dataset) { 353 StringBuilder configFile = new StringBuilder(); 354 preamble(configFile); 355 dataset(configFile, dataset); 356 trainers(configFile); 357 358 int numNeighbors; 359 switch (dataset) 360 { 361 case AEEEM: 362 numNeighbors = 2; 363 break; 364 case MDP: 365 numNeighbors = 5; 366 break; 367 case JURECZKO: 368 numNeighbors = 30; 369 break; 370 case FILTERJURECZKO: 371 numNeighbors = 20; 372 break; 373 case RELINK: 374 numNeighbors = 1; 375 break; 376 case NETGENE: 377 numNeighbors = 1; 378 break; 379 case SELECTEDJURECZKO: 380 numNeighbors = 4; 381 break; 382 default: 383 numNeighbors = 10; 384 break; 385 } 255 386 256 387 configFile.append(" <setwisepreprocessor name=\"Normalization\" param=\"\" />\n"); 257 configFile.append(" <setwiseselector name=\"SetWise EMClusterSelection\" param=\"mean stddev\" />\n");388 configFile.append(" <setwiseselector name=\"SetWiseKNNSelection\" param=\""+ numNeighbors +"\" />\n"); 258 389 configFile.append(" <postprocessor name=\"BiasedWeights\" param=\"0.5\" />\n"); 259 390 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); … … 263 394 } 264 395 265 public static String ZHe 2013(Dataset dataset) {396 public static String ZHe13(Dataset dataset) { 266 397 StringBuilder configFile = new StringBuilder(); 267 398 preamble(configFile); … … 269 400 trainersBagging(configFile); 270 401 402 int numNeighbors; 403 switch (dataset) 404 { 405 case AEEEM: 406 numNeighbors = 1; 407 break; 408 case MDP: 409 numNeighbors = 4; 410 break; 411 case JURECZKO: 412 numNeighbors = 16; 413 break; 414 case FILTERJURECZKO: 415 numNeighbors = 13; 416 break; 417 case RELINK: 418 numNeighbors = 1; 419 break; 420 case NETGENE: 421 numNeighbors = 1; 422 break; 423 case SELECTEDJURECZKO: 424 numNeighbors = 4; 425 break; 426 default: 427 numNeighbors = 10; 428 break; 429 } 430 271 431 configFile.append(" <setwisepreprocessor name=\"Normalization\" param=\"\" />\n"); 272 configFile.append(" <setwiseselector name=\"SeparatabilitySelection\" param=\" \" />\n");432 configFile.append(" <setwiseselector name=\"SeparatabilitySelection\" param=\"" + numNeighbors + "\" />\n"); 273 433 configFile.append(" <setwisepostprocessor name=\"Undersampling\" param=\"\" />\n"); 274 434 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 275 276 postamble(configFile); 277 return configFile.toString(); 278 } 279 280 public static String Nam2013(Dataset dataset) { 435 configFile.append(" <repetitions number=\"10\" />\n"); 436 437 postamble(configFile); 438 return configFile.toString(); 439 } 440 441 public static String Nam13(Dataset dataset) { 281 442 StringBuilder configFile = new StringBuilder(); 282 443 preamble(configFile); … … 292 453 } 293 454 294 public static String Panichella2014(Dataset dataset) { 295 StringBuilder configFile = new StringBuilder(); 296 preamble(configFile); 297 dataset(configFile, dataset); 298 299 configFile.append(" <trainer name=\"WekaTraining\" param=\"LogisticCODEP de.ugoe.cs.cpdp.wekaclassifier.LogisticCODEP\" />\n"); 300 configFile.append(" <trainer name=\"WekaTraining\" param=\"BayesNetCODEP de.ugoe.cs.cpdp.wekaclassifier.BayesNetCODEP\" />\n"); 301 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 302 303 postamble(configFile); 304 return configFile.toString(); 305 } 306 307 // TODO F.Zhang 2014 308 309 // TODO Mizuno 2014: data not public 310 311 public static String Ryu2014(Dataset dataset) { 455 public static String Panichella14(Dataset dataset) { 456 StringBuilder configFile = new StringBuilder(); 457 preamble(configFile); 458 dataset(configFile, dataset); 459 460 configFile.append(" <trainer name=\"WekaTraining\" param=\"CODEP-LR de.ugoe.cs.cpdp.wekaclassifier.LogisticCODEP\" />\n"); 461 configFile.append(" <trainer name=\"WekaTraining\" param=\"CODEP-BN de.ugoe.cs.cpdp.wekaclassifier.BayesNetCODEP\" />\n"); 462 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 463 464 postamble(configFile); 465 return configFile.toString(); 466 } 467 468 public static String Ryu14(Dataset dataset) { 312 469 StringBuilder configFile = new StringBuilder(); 313 470 preamble(configFile); … … 317 474 configFile.append(" <testawaretrainer name=\"WekaTestAwareTraining\" param=\"VCBSVM de.ugoe.cs.cpdp.wekaclassifier.VCBSVM -L 0.1 -B 10\" />\n"); 318 475 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 319 320 postamble(configFile); 321 return configFile.toString(); 322 } 323 324 public static String PHe2015(Dataset dataset) { 476 configFile.append(" <repetitions number=\"10\" />\n"); 477 478 postamble(configFile); 479 return configFile.toString(); 480 } 481 482 public static String PHe15(Dataset dataset) { 325 483 StringBuilder configFile = new StringBuilder(); 326 484 preamble(configFile); … … 336 494 } 337 495 338 // TODO Peters 2015 (LACE2) 339 340 public static String Kawata2015(Dataset dataset) { 496 public static String Peters15(Dataset dataset) { 497 StringBuilder configFile = new StringBuilder(); 498 preamble(configFile); 499 dataset(configFile, dataset); 500 trainers(configFile); 501 502 configFile.append(" <setwisepreprocessor name=\"LogarithmTransform\" param=\"\" />\n"); 503 configFile.append(" <setwiseselector name=\"LACE2\" param=\"0.4\" />\n"); 504 configFile.append(" <pointwiseselector name=\"TurhanFilter\" param=\"1\" />\n"); 505 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 506 configFile.append(" <repetitions number=\"10\" />\n"); 507 508 postamble(configFile); 509 return configFile.toString(); 510 } 511 512 public static String Kawata15(Dataset dataset) { 341 513 StringBuilder configFile = new StringBuilder(); 342 514 preamble(configFile); … … 351 523 } 352 524 353 public static String YZhang 2015(Dataset dataset) {354 StringBuilder configFile = new StringBuilder(); 355 preamble(configFile); 356 dataset(configFile, dataset); 357 358 configFile.append(" <trainer name=\"WekaTraining\" param=\"AVGV ote weka.classifiers.meta.Vote -S 1 -B "weka.classifiers.trees.ADTree" -B "weka.classifiers.rules.DecisionTable" -B "weka.classifiers.bayes.BayesNet" -B "weka.classifiers.functions.MultilayerPerceptron" -B "weka.classifiers.functions.RBFNetwork" -R AVG\" />\n");359 configFile.append(" <trainer name=\"WekaTraining\" param=\"MAXV ote weka.classifiers.meta.Vote -S 1 -B "weka.classifiers.trees.ADTree" -B "weka.classifiers.rules.DecisionTable" -B "weka.classifiers.bayes.BayesNet" -B "weka.classifiers.functions.MultilayerPerceptron" -B "weka.classifiers.functions.RBFNetwork" -R MAX\" />\n");360 configFile.append(" <trainer name=\"WekaTraining\" param=\"BAG GINGC4.5weka.classifiers.meta.Bagging -P 100 -S 1 -I 10 -W weka.classifiers.trees.J48\" />\n");361 configFile.append(" <trainer name=\"WekaTraining\" param=\"BAG GINGNaiveBayesweka.classifiers.meta.Bagging -P 100 -S 1 -I 10 -W weka.classifiers.bayes.NaiveBayes\" />\n");362 configFile.append(" <trainer name=\"WekaTraining\" param=\"BOOST INGC4.5weka.classifiers.meta.AdaBoostM1 -P 100 -S 1 -I 10 -W weka.classifiers.trees.J48\" />\n");363 configFile.append(" <trainer name=\"WekaTraining\" param=\"BOOST INGNaiveBayesweka.classifiers.meta.AdaBoostM1 -P 100 -S 1 -I 10 -W weka.classifiers.bayes.NaiveBayes\" />\n");364 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 365 366 postamble(configFile); 367 return configFile.toString(); 368 } 369 370 public static String Amasaki 2015(Dataset dataset) {525 public static String YZhang15(Dataset dataset) { 526 StringBuilder configFile = new StringBuilder(); 527 preamble(configFile); 528 dataset(configFile, dataset); 529 530 configFile.append(" <trainer name=\"WekaTraining\" param=\"AVGVOTE weka.classifiers.meta.Vote -S 1 -B "weka.classifiers.trees.ADTree" -B "de.ugoe.cs.cpdp.wekaclassifier.DecisionTableWrapper" -B "de.ugoe.cs.cpdp.wekaclassifier.BayesNetWrapper" -B "weka.classifiers.functions.MultilayerPerceptron" -B "weka.classifiers.functions.RBFNetwork" -R AVG\" />\n"); 531 configFile.append(" <trainer name=\"WekaTraining\" param=\"MAXVOTE weka.classifiers.meta.Vote -S 1 -B "weka.classifiers.trees.ADTree" -B "de.ugoe.cs.cpdp.wekaclassifier.DecisionTableWrapper" -B "de.ugoe.cs.cpdp.wekaclassifier.BayesNetWrapper" -B "weka.classifiers.functions.MultilayerPerceptron" -B "weka.classifiers.functions.RBFNetwork" -R MAX\" />\n"); 532 configFile.append(" <trainer name=\"WekaTraining\" param=\"BAG-DT weka.classifiers.meta.Bagging -P 100 -S 1 -I 10 -W weka.classifiers.trees.J48\" />\n"); 533 configFile.append(" <trainer name=\"WekaTraining\" param=\"BAG-NB weka.classifiers.meta.Bagging -P 100 -S 1 -I 10 -W weka.classifiers.bayes.NaiveBayes\" />\n"); 534 configFile.append(" <trainer name=\"WekaTraining\" param=\"BOOST-DT weka.classifiers.meta.AdaBoostM1 -P 100 -S 1 -I 10 -W weka.classifiers.trees.J48\" />\n"); 535 configFile.append(" <trainer name=\"WekaTraining\" param=\"BOOST-NB weka.classifiers.meta.AdaBoostM1 -P 100 -S 1 -I 10 -W weka.classifiers.bayes.NaiveBayes\" />\n"); 536 configFile.append(" <eval name=\"NormalWekaEvaluation\" param=\"\" />\n"); 537 538 postamble(configFile); 539 return configFile.toString(); 540 } 541 542 public static String Amasaki15(Dataset dataset) { 371 543 StringBuilder configFile = new StringBuilder(); 372 544 preamble(configFile); … … 383 555 } 384 556 385 public static String Ryu 2015b(Dataset dataset) {557 public static String Ryu15(Dataset dataset) { 386 558 StringBuilder configFile = new StringBuilder(); 387 559 preamble(configFile); … … 397 569 } 398 570 399 // TODO Cao 2015 400 401 public static String Nam2015b(Dataset dataset) { 571 public static String Nam15(Dataset dataset) { 402 572 StringBuilder configFile = new StringBuilder(); 403 573 preamble(configFile);
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