Get Started with Statistics and Machine Learning Toolbox
R2026bStatistics and Machine Learning Toolbox™ provides functions and apps for statistical analysis and machine learning in MATLAB®.
For statistical analysis, you can use descriptive statistics to explore data, fit probability distributions, test hypotheses, perform analysis of variance (ANOVA), plan experiments, validate measurement systems, and monitor processes. You can use functions for programmatic analysis and interactive apps for guided workflows such as distribution fitting, design of experiments (DOE), and Gage R&R.
For machine learning, you can train regression, classification, clustering, and other models interactively or programmatically. The toolbox supports feature engineering, dimensionality reduction, model interpretation, Simulink® integration, and C/C++ code generation for deployment. For an interactive experience, you can use the Classification Learner or Regression Learner apps to explore data, select features, choose validation schemes, tune hyperparameters, and evaluate multiple algorithms side-by-side.
Tutorials
- Exploratory Analysis of Data
Explore the distribution of data using visualizations and descriptive statistics.
- Hypothesis Testing with Two Samples
Use hypothesis testing to analyze gas prices measured across the state of Massachusetts during two separate months.
- Evaluate Optimal Number of Clusters
Identify the optimal number of clusters in a data set by using the
evalclustersfunction. - Assess Regression Neural Network Performance
Use
fitrnetto create a feedforward regression neural network model with fully connected layers, and assess the performance of the model on test data. - Train Decision Trees Using Classification Learner App
Create and compare classification trees, and export trained models to make predictions for new data.
About Machine Learning
- Machine Learning in MATLAB
Discover machine learning capabilities in MATLAB for classification, regression, clustering, and deep learning, including apps for automated model training and code generation.
Interactive Learning
Statistics Onramp
Free one-hour online statistics course
Machine Learning Onramp
Free two-hour online machine learning course
Teaching Resources
Machine Learning for Biosciences
Learn the basics of machine learning with biologically motivated examples.
Machine Learning for Regression
Learn the concepts of feature extraction and regression and apply them to time series forecasting.
