- fitcdiscr: Trains a single multiclass classifier directly, without decomposing the problem into binary subproblems.
- fitcecoc: Uses the Error Correcting Output Codes (ECOC) approach, decomposing the multiclass problem into multiple binary subproblems
- fitcdiscr: Trains a single multiclass classifier.
- fitcecoc: Trains multiple binary classifiers, one for each binary subproblem.
- fitcdiscr: Uses the specified discriminant analysis algorithm to directly solve the multiclass problem.
- fitcecoc: Solves the multiclass problem by combining the predictions of the binary classifiers trained for each subproblem.
- fitcdiscr: Provides a simpler and more straightforward approach when you want to use a specific discriminant analysis algorithm for multiclass classification.
- fitcecoc: Offers more flexibility by allowing you to choose different binary classifiers and leverage their strengths for multiclass classification.
- fitcdiscr: Performance depends on the discriminant analysis algorithm chosen and its suitability for the problem.
- fitcecoc: Performance can be influenced by the choice of binary classifiers and their ability to handle the binary subproblems effectively.
- fitcdiscr: Provides direct interpretability of the multiclass classification results.
- fitcecoc: Requires interpreting the results of multiple binary classifiers to understand the multiclass classification outcome.