public CrossFoldLearner copy() { CrossFoldLearner r = new CrossFoldLearner(models.size(), numCategories(), numFeatures, prior); r.models.clear(); for (OnlineLogisticRegression model : models) { model.close(); OnlineLogisticRegression newModel = new OnlineLogisticRegression(model.numCategories(), model.numFeatures(), model.prior); newModel.copyFrom(model); r.models.add(newModel); } return r; }
public CrossFoldLearner copy() { CrossFoldLearner r = new CrossFoldLearner(models.size(), numCategories(), numFeatures, prior); r.models.clear(); for (OnlineLogisticRegression model : models) { model.close(); OnlineLogisticRegression newModel = new OnlineLogisticRegression(model.numCategories(), model.numFeatures(), model.prior); newModel.copyFrom(model); r.models.add(newModel); } return r; }
public CrossFoldLearner copy() { CrossFoldLearner r = new CrossFoldLearner(models.size(), numCategories(), numFeatures, prior); r.models.clear(); for (OnlineLogisticRegression model : models) { model.close(); OnlineLogisticRegression newModel = new OnlineLogisticRegression(model.numCategories(), model.numFeatures(), model.prior); newModel.copyFrom(model); r.models.add(newModel); } return r; }
public OnlineLogisticRegression copy() { close(); OnlineLogisticRegression r = new OnlineLogisticRegression(numCategories(), numFeatures(), prior); r.copyFrom(this); return r; }
public OnlineLogisticRegression copy() { close(); OnlineLogisticRegression r = new OnlineLogisticRegression(numCategories(), numFeatures(), prior); r.copyFrom(this); return r; }
public OnlineLogisticRegression copy() { close(); OnlineLogisticRegression r = new OnlineLogisticRegression(numCategories(), numFeatures(), prior); r.copyFrom(this); return r; }