Metrics
Learn which metrics to use for a machine learning use case and model. MAPE,RMSE,MAE,MDAPE,precision, recall, and many more metrics explained simply
How to interpret F1 score (simply explained) Paid Members Public
F1 score is a common classification machine learning metric, but it can be confusing to know how to interpret the values. In this post, I explain what F1 is, how to interpret the values and walk through an example.
How to interpret MAPE (simply explained) Paid Members Public
MAPE (Mean Absolute Percentage Error) is a common regression machine learning metric, but it can be confusing to know how to interpret the values. In this post, I explain what MAPE is, how to interpret the values and walk through an example.
What is a good MAPE score? Paid Members Public
MAPE (Mean Absolute Percentage Error) is a common regression machine learning metric, but it can be confusing to know what a good score actually is. In this post, I explain what MAPE is, what a good score is, and answer some common questions that people have.
MDAPE (median absolute percentage error) explained! Paid Members Public
Median Absolute Percentage Error (MDAPE) is an error metric for regression machine learning models, but it’s not widely understood. In this post, I explain what MDAPE is, how to calculate it, and what a good value is.
What is a good R-Squared value? (simply explained) Paid Members Public
R-Squared is a metric used in machine learning and statistics, but it can be confusing to know what a good value is. In this post, I explain what R-Squared is, how to calculate it, and what a good value actually is.
What is a good MSE value? (simply explained) Paid Members Public
Mean Squared Error (MSE) is a machine learning metric for regression models, but it can be confusing to know what a good value is. In this post, I will explain what MSE is, how to calculate it, and what a good value actually is.
What is a good AUC score? (simply explained) Paid Members Public
AUC score (also known as ROC AUC score) is a classification machine learning metric, but it can be confusing to know what a good score is. In this post, I explain what AUC score is, how to calculate it, and what a good score actually is.
What is imbalanced data? Simply explained Paid Members Public
Imbalanced data is a common occurrence when working with classification machine learning models. In this post, I explain what imbalanced data is and answer common questions that people have.
