![]() ![]() ![]() The toolbox provides supervised, semi-supervised, and unsupervised machine learning algorithms, including support vector machines (SVMs), boosted decision trees, shallow neural nets, k-means, and other clustering methods. ![]() Regression and classification algorithms let you draw inferences from data and build predictive models either interactively, using the Classification and Regression Learner apps, or programmatically, using AutoML.įor multidimensional data analysis and feature extraction, the toolbox provides principal component analysis (PCA), regularization, dimensionality reduction, and feature selection methods that let you identify variables with the best predictive power. You can use descriptive statistics, visualizations, and clustering for exploratory data analysis fit probability distributions to data generate random numbers for Monte Carlo simulations, and perform hypothesis tests. Statistics and Machine Learning Toolbox™ provides functions and apps to describe, analyze, and model data. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
June 2023
Categories |