CODE EXAMPLE FOR PYTHON

K fold Cross Validation

# K-Fold Cross-Validation
from sklearn.model_selection import cross_validate
def cross_validation(model, _X, _y, _cv=5):
      '''Function to perform 5 Folds Cross-Validation
       Parameters
       ----------
      model: Python Class, default=None
              This is the machine learning algorithm to be used for training.
      _X: array
           This is the matrix of features.
      _y: array
           This is the target variable.
      _cv: int, default=5
          Determines the number of folds for cross-validation.
       Returns
       -------
       The function returns a dictionary containing the metrics 'accuracy', 'precision',
       'recall', 'f1' for both training set and validation set.
      '''
      _scoring = ['accuracy', 'precision', 'recall', 'f1']
      results = cross_validate(estimator=model,
                               X=_X,
                               y=_y,
                               cv=_cv,
                               scoring=_scoring,
                               return_train_score=True)
      
      return {"Training Accuracy scores": results['train_accuracy'],
              "Mean Training Accuracy": results['train_accuracy'].mean()*100,
              "Training Precision scores": results['train_precision'],
              "Mean Training Precision": results['train_precision'].mean(),
              "Training Recall scores": results['train_recall'],
              "Mean Training Recall": results['train_recall'].mean(),
              "Training F1 scores": results['train_f1'],
              "Mean Training F1 Score": results['train_f1'].mean(),
              "Validation Accuracy scores": results['test_accuracy'],
              "Mean Validation Accuracy": results['test_accuracy'].mean()*100,
              "Validation Precision scores": results['test_precision'],
              "Mean Validation Precision": results['test_precision'].mean(),
              "Validation Recall scores": results['test_recall'],
              "Mean Validation Recall": results['test_recall'].mean(),
              "Validation F1 scores": results['test_f1'],
              "Mean Validation F1 Score": results['test_f1'].mean()
              }