| 321 | } |
| 322 | |
| 323 | @Override |
| 324 | public void train(RegressionDataSet dataSet, ExecutorService threadPool) |
| 325 | { |
| 326 | final int models = baseRegressors.size(); |
| 327 | weightsPerModel = 1; |
| 328 | RegressionDataSet metaSet = new RegressionDataSet(models, new CategoricalData[0]); |
| 329 | |
| 330 | List<RegressionDataSet> dataFolds = dataSet.cvSet(folds); |
| 331 | //iterate in the order of the folds so we get the right dataum weights |
| 332 | for(RegressionDataSet rds : dataFolds) |
| 333 | for(int i = 0; i < rds.getSampleSize(); i++) |
| 334 | metaSet.addDataPoint(new DataPoint(new DenseVector(weightsPerModel*models), rds.getDataPoint(i).getWeight()), rds.getTargetValue(i)); |
| 335 | |
| 336 | //create the meta training set |
| 337 | for(int c = 0; c < baseRegressors.size(); c++) |
| 338 | { |
| 339 | Regressor reg = baseRegressors.get(c); |
| 340 | int pos = 0; |
| 341 | for(int f = 0; f < dataFolds.size(); f++) |
| 342 | { |
| 343 | RegressionDataSet train = RegressionDataSet.comineAllBut(dataFolds, f); |
| 344 | RegressionDataSet test = dataFolds.get(f); |
| 345 | if(threadPool == null) |
| 346 | reg.train(train); |
| 347 | else |
| 348 | reg.train(train, threadPool); |
| 349 | for(int i = 0; i < test.getSampleSize(); i++)//evaluate and mark each point in the held out fold. |
| 350 | { |
| 351 | double pred = reg.regress(test.getDataPoint(i)); |
| 352 | |
| 353 | metaSet.getDataPoint(pos++).getNumericalValues().set(c, pred); |
| 354 | } |
| 355 | } |
| 356 | } |
| 357 | |
| 358 | //train the meta model |
| 359 | if(threadPool == null) |
| 360 | aggregatingRegressor.train(metaSet); |
| 361 | else |
| 362 | aggregatingRegressor.train(metaSet, threadPool); |
| 363 | |
| 364 | //train the final classifiers, unless folds=1. In that case they are already trained |
| 365 | if(folds != 1) |
| 366 | { |
| 367 | for(Regressor reg : baseRegressors) |
| 368 | if(threadPool == null) |
| 369 | reg.train(dataSet); |
| 370 | else |
| 371 | reg.train(dataSet, threadPool); |
| 372 | } |
| 373 | } |
| 374 | |
| 375 | @Override |
| 376 | public void train(RegressionDataSet dataSet) |