# Matlab Use Machine Learning Apps

Use when the user wants to train, compare, or export machine learning models using...

- Repository: https://github.com/matlab/matlab-agentic-toolkit (1237 stars)
- Category: Testing
- License: see repository
- Last updated: 2026-10-27
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-machine-learning-apps -g -a claude-code -y`
Codex: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-machine-learning-apps -g -a codex -y`
Cursor: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-machine-learning-apps -g -a cursor -y`
Gemini CLI: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-machine-learning-apps -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add matlab/matlab-agentic-toolkit`

## Description

Use when the user wants to train, compare, or export machine learning models using Classification Learner or Regression Learner, including opening the app, loading data, training models, evaluating metrics, comparing results, visualizing plots, testing on held-out data, exploring model interpretability, and exporting trained models. Programmatic access to Classification Learner and Regression Learner apps via AppController.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Learner Apps AppController Reference

`mlearnapp.internal.appcontroller.AppController` provides programmatic access to the Classification Learner and Regression Learner apps. Use it to interact with learner apps and query their state.

Source (loaded at runtime): `<skill-base-directory>/scripts/+mlearnapp/+internal/+appcontroller/AppController.p`

### API Reference (load on demand)

| When you need... | Load this file |
|------------------|---------------|
| Open/close/save/load app, session setup, create/train/select/delete models, model status, GalleryModels enum | [`api-session-and-models.md`](references/api-session-and-models.md) |
| Metrics, model spec queries, toolstrip buttons, set feature selection/PCA/optimizer/cost/hyperparameters | [`api-metrics-and-options.md`](references/api-metrics-and-options.md) |
| Open/configure standard plots, results table, standard plot data getters | [`api-plots.md`](references/api-plots.md) |
| PDP, permutation importance, Shapley, LIME, Set Shapley Parameters, explainability plot data getters | [`api-explainability.md`](references/api-explainability.md) |
| Export methods, command logging, diagnostics | [`api-export-and-diagnostics.md`](references/api-export-and-diagnostics.md) |

**Required:** Statistics and Machine Learning Toolbox. **Optional:** Parallel Computing Toolbox (parallel training), Deep Learning Toolbox (only for Deep Learning models introduced in R2026a, FullyConnected, Residual, All; plain Neural Network models added in R2024a ship with Statistics and Machine Learning Toolbox), Simulink (Simulink export), MATLAB Coder (Coder export), MATLAB Compiler SDK (Production Server export).

## When to Use

The rest: https://github.com/matlab/matlab-agentic-toolkit/blob/HEAD/skills-catalog/ai-and-statistics/matlab-use-machine-learning-apps/SKILL.md