Statistics and Machine Learning
R2026bGenerate portable C/C++ code from trained machine learning models and statistical algorithms for deployment to embedded systems, enterprise applications, and edge devices. These examples demonstrate end-to-end workflows for compiling classification, regression, and clustering algorithms into standalone executables or libraries that run independently of MATLAB®.
Featured Examples
Code Generation for Prediction of Machine Learning Model Using MATLAB Coder App
Generate code for the prediction of a classification or regression model by using the MATLAB Coder™ app.
Code Generation for Prediction of Machine Learning Model at Command Line
Generate code for the prediction of a classification or regression model at the command line.
Code Generation for Incremental Learning
Generate code that implements incremental learning for binary linear classification at the command line.
Generate Code to Classify Data in Table
Generate code for classifying data in a table containing numeric and categorical variables.
Code Generation for Nearest Neighbor Searcher
Generate code for finding nearest neighbors using a nearest neighbor searcher model.
Code Generation for Probability Distribution Objects
Generate code that fits a probability distribution object to sample data and evaluates the fitted distribution object.
