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Discriminant Analysis

Regularized linear and quadratic discriminant analysis

To interactively train a discriminant analysis model, use the Classification Learner app. For greater flexibility, train a discriminant analysis model using fitcdiscr in the command-line interface. After training, predict labels or estimate posterior probabilities by passing the model and predictor data to predict.


Classification Learner Train models to classify data using supervised machine learning


fitcdiscr Fit discriminant analysis classifier
predict Predict labels using discriminant analysis classification model
templateDiscriminant Discriminant analysis classifier template


ClassificationDiscriminant Discriminant analysis classification
CompactClassificationDiscriminant Compact discriminant analysis class
ClassificationPartitionedModel Cross-validated classification model

Examples and How To

Train Discriminant Analysis Classifiers Using Classification Learner App

Learn how to train discriminant analysis classifiers.

Steps in Supervised Learning

While there are many Statistics and Machine Learning Toolbox™ algorithms for supervised learning, most use the same basic workflow for obtaining a predictor model.

Create Discriminant Analysis Classifiers

Train a basic discriminant analysis classifier to classify irises in Fisher's iris data.

Create and Visualize Discriminant Analysis Classifier

Perform linear and quadratic classification of Fisher iris data.

Improve a Discriminant Analysis Classifier

Examine and improve discriminant analysis classifier performance.

Regularize a Discriminant Analysis Classifier

Make a more robust and simpler model by trying to remove predictors without hurting the predictive power of the model.

Examine the Gaussian Mixture Assumption

Discriminant analysis assumes that the data comes from a Gaussian mixture model. Learn how to examine this assumption.


Characteristics of Classification Algorithms

Classification algorithms vary in speed, memory usage, interpretability, and flexibility.

What Is Discriminant Analysis?

Discriminant analysis is a classification method which assumes that different classes generate data based on different Gaussian distributions.

Creating a Classifier Using fitcdiscr

Understand the algorithm used to construct weighted classifiers.

How the predict Method Classifies

predict uses three quantities to classify observations: posterior probability, prior probability, and cost.

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