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Reference Guides
Reference guides are available for functions and commands supported by OML, Tcl, and Python.
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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What's New
Discover new features and enhancements.
Get Started
Discover Compose, including its language support and system requirements.
Tutorials
The Compose tutorials and associated example model files help introduce you to the basic functionality of the software.
User Guide
Learn about the features and functionality available in Compose.
Reference Guides
Reference guides are available for functions and commands supported by OML, Tcl, and Python.
- 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
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  - Machine Learning Commands
    - 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
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  - Time Commands
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  - OML to Python Bridge Commands
  - Python to OML Bridge Commands
- Python in Compose Reference Guide

Home
Reference Guides
Reference guides are available for functions and commands supported by OML, Tcl, and Python.
Reference Guide for OpenMatrix Language Functions
The Reference Guide contains documentation for all functions supported in the OpenMatrix language.
Machine Learning Commands
Clustering

What's New
Get Started
Tutorials
User Guide
Reference Guides

Clustering

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

Agglomerative
KMeans

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.

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