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///////////////////////////////////////////////////////////////////////////////
//Copyright (C) 2014 Joliciel Informatique
//
//This file is part of Talismane.
//
//Talismane is free software: you can redistribute it and/or modify
//it under the terms of the GNU Affero General Public License as published by
//the Free Software Foundation, either version 3 of the License, or
//(at your option) any later version.
//
//Talismane 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 Affero General Public License for more details.
//
//You should have received a copy of the GNU Affero General Public License
//along with Talismane.  If not, see .
//////////////////////////////////////////////////////////////////////////////
package com.joliciel.talismane.machineLearning;

import com.joliciel.talismane.machineLearning.linearsvm.LinearSVMModelTrainer;
import com.joliciel.talismane.machineLearning.maxent.MaxentModelTrainer;
import com.joliciel.talismane.machineLearning.perceptron.PerceptronClassificationModelTrainer;
import com.joliciel.talismane.utils.JolicielException;
import com.typesafe.config.Config;
import com.typesafe.config.ConfigFactory;

/**
 * A class for constructing model trainers implementing ModelTrainer.
 * 
 * @author Assaf Urieli
 *
 */
public class ModelTrainerFactory {
  /**
   * Get a classification model trainer corresponding to a given outcome type
   * and a given algorithm.

   * 

   * It is assumed the config file passed will be a local configuration, whose
   * root is equivalent to the talismane.machine-learning key in reference.conf
   */
  public ClassificationModelTrainer constructTrainer(Config config) {
    config.checkValid(ConfigFactory.defaultReference().getConfig("talismane.machine-learning.generic"));
    MachineLearningAlgorithm algorithm = MachineLearningAlgorithm.valueOf(config.getString("algorithm"));
    ClassificationModelTrainer modelTrainer = null;
    switch (algorithm) {
    case MaxEnt:
      MaxentModelTrainer maxentModelTrainer = new MaxentModelTrainer();
      modelTrainer = maxentModelTrainer;
      break;
    case LinearSVM:
    case LinearSVMOneVsRest:
      LinearSVMModelTrainer linearSVMModelTrainer = new LinearSVMModelTrainer();
      modelTrainer = linearSVMModelTrainer;
      break;
    case Perceptron:
      PerceptronClassificationModelTrainer perceptronModelTrainer = new PerceptronClassificationModelTrainer();
      modelTrainer = perceptronModelTrainer;
      break;
    default:
      throw new JolicielException("Machine learning algorithm not yet supported: " + algorithm);
    }

    modelTrainer.setParameters(config);
    return modelTrainer;
  }
}