How to calculate Machine Learning Performance

There are several different calculations you can use to assess the reliability of your machine learning. You’ll need to understand your machine learning’s true and false positives and negatives based on actual and predicted classifications. Some examples of calculations you can do to achieve this are: Recall (or sensitivity) - How many times a positive prediction was made by a model. Accuracy - How the model performs across all classes Precision - The quality of a positive prediction made by a model. Logarithmic loss - How close a prediction probability is to its true value.