text: import os
  from pathlib import Path
  import joblib
  import pandas as pd
  import numpy as np
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import cross_validate
  
  
  root_folder = Path(os.path.dirname(os.path.dirname(__file__)))
  training_data = root_folder / 'data' / 'processed' / 'train.csv'
  model_folder = root_folder / 'models'  
  model_file = model_folder / 'classifier.bin'
  
  df = pd.read_csv(training_data)
  x = df.drop(['LABEL'], axis=1)
  y = df['LABEL']
  
  model = RandomForestClassifier()
  results = cross_validate(model, x, y, cv=5, return_estimator=True)
  
  os.makedirs(model_folder, exist_ok=True)
  
  best_estimator = results['estimator'][np.argmax(results['test_score'])]
  joblib.dump(best_estimator, model_file)
  
  print(f"Done training. Stored model with score: {np.max(results['test_score'])}")