ICluster interface

This article describes ICluster, which is the interface for trained clustering models that is used in Azure Machine Learning Studio (classic).


Applies to: Machine Learning Studio (classic)

This content pertains only to Studio (classic). Similar drag and drop modules have been added to Azure Machine Learning designer (preview). Learn more in this article comparing the two versions.

The ICluster interface provides methods and properties that are used to configure and interact with clustering models. A learner is defined as a set of instructions that perform standardized machine learning tasks.

The ICluster interface provides the following methods and properties for working with clustering models:

  • Gets or sets the feature attributes
  • Trains a clustering model from data
  • Applies a clustering model to new data

You can interact with ICluster only in Studio (classic), or in one of the supported APIs.

For classification or regression models, use the iLearner interface.

See also

Module data types