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.
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.
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.