Attention A T users. To access the menus on this page please perform the following steps. 1. Please switch auto forms mode to off. 2. Hit enter to expand a main menu option (Health, Benefits, etc). 3. To enter and activate the submenu links, hit the down arrow. You will now be able to tab or arrow up or down through the submenu options to access/activate the submenu links.

VA Technical Reference Model v 24.3

Statistics and Machine Learning Toolbox
Statistics and Machine Learning Toolbox Technology

General InformationGeneral Information help

Technologies must be operated and maintained in accordance with Federal and Department security and privacy policies and guidelines. More information on the proper use of the TRM can be found on the TRM Proper Use Tab/Section.

Website: Go to site
Description: Statistics and Machine Learning Toolbox provides functions to describe, analyze, and model data. Users can use descriptive statistics and plots to perform exploratory data analysis, fit probability distributions to data, generate random numbers for Monte Carlo simulations, and perform hypothesis tests. Regression and classification algorithms enable users draw inferences from data and build predictive models.

For multidimensional data analysis, Statistics and Machine Learning Toolbox provides feature selection, stepwise regression, principal component analysis (PCA), regularization, and other dimensionality reduction methods that let users identify variables or features that impact their models. This technology also provides supervised and unsupervised machine learning algorithms, including support vector machines (SVMs), boosted and bagged decision trees, k-nearest neighbor, k-means, k-medoids, hierarchical clustering, Gaussian mixture models, and hidden Markov models.

This technology does not utilize a database, as all data is saved to the user`s local drive.

The TRM decisions in this entry only apply to technologies and versions owned, operated, managed, patched, and version-controlled by VA. This includes technologies deployed as software installations on VMs within VA-controlled cloud environments (e.g., VA Enterprise Cloud (VAEC)). Cloud services provided by the VAEC, which are listed in the VAEC Service Catalog, and those controlled and managed by an external Cloud Service Provider (i.e., SaaS) are not in the purview of the TRM. For more information on the use of cloud services and cloud-based products within VA, including VA private clouds, please see the Enterprise Cloud Solutions Office (ECSO) Portal at: https://dvagov.sharepoint.com/sites/OITEPMOECSO
Technology/Standard Usage Requirements: Users must ensure their use of this technology/standard is consistent with VA policies and standards, including, but not limited to, VA Handbooks 6102 and 6500; VA Directives 6004, 6513, and 6517; and National Institute of Standards and Technology (NIST) standards, including Federal Information Processing Standards (FIPS). Users must ensure sensitive data is properly protected in compliance with all VA regulations. Prior to use of this technology, users should check with their supervisor, Information Security Officer (ISO), Facility Chief Information Officer (CIO), or local Office of Information and Technology (OI&T) representative to ensure that all actions are consistent with current VA policies and procedures prior to implementation.
Section 508 Information: This technology has been assessed by the Section 508 Office and found non-conformant. The Implementer of this technology has the responsibility to ensure the version deployed is 508-compliant. Section 508 compliance may be reviewed by the Section 508 Office and appropriate remedial action required if necessary. For additional information or assistance regarding Section 508, please contact the Section 508 Office at Section508@va.gov. Please see reference tab for more information concerning product versions.
Decision: View Decisions

Decision Source: TRM Mgmt Group
Decision Process: One-VA TRM v23.5
Decision Date: 05/09/2023 at 19:44:08 UTC
Introduced By: TRM Request
Vendor Name: MathWorks
- The information contained on this page is accurate as of the Decision Date (05/09/2023 at 19:44:08 UTC).