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Explore the Extended Definitions, OML Guides, Block Library, API Guide and Glossary.
Reference Guide for OpenMatrix Language Functions
The Reference Guide contains documentation for all functions supported in the OpenMatrix language.
Machine Learning Commands
Clustering

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Reference Guides
Explore the Extended Definitions, OML Guides, Block Library, API Guide and Glossary.
- Extended Definitions for Advanced Users
  PDF file with in-depth information on key topics in the User's Guide.
- Scripting Guide for OpenMatrix Language
  OpenMatrix is a mathematical scripting language.
- Reference Guide for OpenMatrix Language Functions
  The Reference Guide contains documentation for all functions supported in the OpenMatrix language.
  - ABF Commands
  - Altair Integration Commands
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  - hstpyfit Commands
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  - JSON Commands
  - Library Manager Commands
  - Linear Algebra Commands
  - Logical Commands
  - Machine Learning Commands
    - Apriori
    - Association Rules
    - Classification
    - Clustering
      - agglomerativefit
        Agglomerative clustering. It is an unsupervised learning algorithm. It recursively merges the pair of clusters that minimally increase a given linkage distance.
      - agglomerativepredict
        Predicts target values for the test data points using parameters computed by agglomerativeFit function. In agglomerative clustering, again fitting is done with the given test data points and the options set during training. So instead can use the labels of the output of fit method.
      - kmeansfit
        K-Means clustering. It's an unsupervised learning algorithm.
      - kmeanspredict
        Predicts target values for the test data points using parameters computed by kmeansFit function.
    - Decomposition
    - Distance
    - Evaluation Metrics
    - K-Mode Clustering
    - Model Selection
    - Preprocessing
    - Regression
  - Optimization Commands
  - Plotting Commands
  - Polynomial Math Commands
  - Signal Processing Commands
  - Statistical Analysis Commands
  - String Operations Commands
  - System Commands
  - Table Commands
  - Time Commands
  - Trigonometry Commands
  - OML to Python Bridge Commands
  - Python to OML Bridge Commands
- Block Reference Guide
  Describes all of the blocks in the installed Twin Activate library.
- Function Guide for Twin Activate
  Provides information about developing and simulating models through the Twin Activate Application Program Interface.
- Glossary
  Key terms associated with the software.
Frequently Asked Questions
You've got questions? We've got answers!

Clustering

Attention: Available only with Twin Activate commercial edition.

The clustering, which is the unsupervised grouping task of unlabelled data, can be carried out using the following methods:

Agglomerative
KMeans