text: import pandas as pd 
  from sklearn.model_selection import train_test_split
  from plpred.models import BaseModel, PlpredRF, PlpredGB, PlpredSVM, PlpredNN
  import argparse 
  
  def train_model(file_path:str, model:BaseModel) -> BaseModel:
      """
      Train a ML model to classify membrane proteins.
      Parameters
      ----------
      file_path:str
          path to the preprocessed dataset.
      model: BaseModel
          model to be trained.
      
      Returns
      -------
      model: BaseModel
          trained model.
      report: str
          classification report of the trained model.
      """
      df = pd.read_csv(file_path)
      X = df.drop(['membrane'], axis=1)
      y = df['membrane']
  
      X_train, X_test, y_train, y_test  = train_test_split(X, y)
  
      model.fit(X_train, y_train)
      report = model.validate(X_test, y_test)
  
      return model, report
  
  def main():
  
      models = {
          'random_forest': PlpredRF(),
          'neural_network': PlpredNN(),
          'gradient_boosting': PlpredGB(),
          'svm': PlpredSVM()
      }
  
      argument_parser = argparse.ArgumentParser(description='plpred-train: model training tool')
      argument_parser.add_argument('-p', '--processed_dataset', required=True, help='processed dataset generated by plpred-preprocess (.csv)')
      argument_parser.add_argument('-o', '--output', required=True, help='path to the output trained model (.pickle)')
      argument_parser.add_argument('-r', '--report', default=False, action='store_true', help='show classification report')
      argument_parser.add_argument('-a', '--algorithm', default='random_forest', choices=['random_forest', 'neural_network', 'gradient_boosting', 'svm'], help='machine learning algorithm')
  
      arguments = argument_parser.parse_args()
  
      model, report = train_model(file_path=arguments.processed_dataset, model=models[arguments.algorithm])
      model.save(arguments.output)
  
      if arguments.report:
          print(report)
  
  if __name__ == "__main__":
      main()