code: def create_generic(numeric_values, textual_values, target, algorithm = util_functions.AlgorithmTypes.regression):
      
  
      algorithm = select_algorithm(target)
      #Initialize a result dictionary to return.
      results = {'errors': [],'success' : False, 'cv_kappa' : 0, 'cv_mean_absolute_error': 0,
                 'feature_ext' : "", 'classifier' : "", 'algorithm' : algorithm}
  
      if len(numeric_values)!=len(textual_values) or len(numeric_values)!=len(target):
          msg = "Target, numeric features, and text features must all be the same length."
          results['errors'].append(msg)
          log.exception(msg)
          return results
  
      try:
          #Initialize a predictor set object that encapsulates all of the text and numeric predictors
          pset = predictor_set.PredictorSet(essaytype="train")
          for i in xrange(0, len(numeric_values)):
              pset.add_row(numeric_values[i], textual_values[i], target[i])
      except:
          msg = "predictor set creation failed."
          results['errors'].append(msg)
          log.exception(msg)
  
      try:
          #Extract all features and then train a classifier with the features
          feature_ext, classifier, cv_error_results = model_creator.extract_features_and_generate_model_predictors(pset, algorithm)
          results['cv_kappa']=cv_error_results['kappa']
          results['cv_mean_absolute_error']=cv_error_results['mae']
          results['feature_ext']=feature_ext
          results['classifier']=classifier
          results['success']=True
      except:
          msg = "feature extraction and model creation failed."
          results['errors'].append(msg)
          log.exception(msg)
  
      return results
docs: Creates a model from a generic list numeric values and text values
      numeric_values - A list of lists that are the predictors
      textual_values - A list of lists that are the predictors
      (each item in textual_values corresponds to the similarly indexed counterpart in numeric_values)
      target - The variable that we are trying to predict.  A list of integers.
      algorithm - the type of algorithm that will be used