Glossary Archives - Page 2 of 10

Area under the ROC Curve (AUC)

Written by Evispot. Posted in a, Glossary.

The AUC is the area under the ROC curve and is a performance measure that tells you how well your model can classify different classes. The higher the AUC the better the model.

F1-score

Written by Evispot. Posted in f, Glossary.

In theory a good model (one that makes the right predictions) will be one that has both high precision, as well as high recall. In practice however, a model has to make compromises between both metrics. Thus, it can be hard to compare the performance...

Accuracy

Written by Evispot. Posted in a, Glossary.

Accuracy is a performance metric that allows you to evaluate how good your model is. It’s used in classification models and is the ratio of: Tip: Accuracy is highly sensitive to class imbalances in your data.

False Negatives (FN)

Written by Evispot. Posted in f, Glossary.

Assume a data set that includes examples of a class Non-default and examples of class Default. Assume further that you’re evaluating your model’s performance to predict examples of class Non-default.False negatives is a field in the confusion...

False Positive (FP)

Written by Evispot. Posted in f, Glossary.

True Negatives (TN)

Written by Evispot. Posted in Glossary, t.

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