Helpful and easy to understand guides for machine learning metrics.
Regression machine learning metrics
What is a good MSE score?
What is a good RMSE value?
What is a good MAE score?
What is a good R2 score?
What is a good MAPE score?
How to calculate MAPE with 0 values
What is MDAPE and how do I calculate it in Python?
Can percent error be negative?
Regression metric comparisons
RMSE vs MAE, which should I use?
RMSE vs MSE, what's the difference?
MAE vs MAPE, which is best?
RMSE vs MAPE, which is the best regression metric?
MSE vs MAE, which is the better regression metric?
Regression metric calculators
MSE calculator
RMSE calculator
MAPE calculator
MAE calculator
R squared calculator
Coefficient of determination calculator
Classification machine learning metrics
What is a good F1 score?
What is a good ROC AUC score?
What is a good accuracy score in machine learning?
Balanced accuracy for machine learning
Classification metrics comparisons
AUC vs accuracy, which is the best metric?
Accuracy vs balanced accuracy, which is the best metric?
F1 score vs AUC, which is the best classification metric?
F1 score vs accuracy, which is the best classification metric?
Micro vs Macro F1 score, what’s the difference?
Classification metric calculators
F1 score calculator
Accuracy calculator
Precision recall calculator
Confusion matrix calculator
Confusion matrix maker
Metric advice when creating machine learning models
What is a baseline machine learning model?
What is a good performance metric for clustering algorithms?
What is the best classification metric for imbalanced data?
Loss and cost functions
L1 loss function
L2 loss function
L1 vs L2 loss functions
Loss function vs cost function, what’s the difference?
Model validation
Using cross_val_score in sklearn
Using cross_validate in sklearn
Difference between cross_val_score and cross_validate