Mastering Python for Finance - Second Edition

Quadratic discriminant analysis

Quadratic discriminant analysis (QDA) is very similar to LDA, but uses a quadratic decision boundary and each class uses its own estimate of variance. Running the risk metrics shows that the QDA model does not necessarily give better performance than the LDA model. The type of decision boundary has to be taken into consideration for the model required. QDA is better suited for large datasets, as it tends to have a lower bias and higher variance. On the other hand, LDA is suitable for smaller datasets that have a lower bias and a higher variance.

The QuadraticDiscriminantAnalysis class of the sklearn.discriminant_analysis module implements the QDA model.