This article describes
iLearner, which is the interface for trained models that is used in Azure Machine Learning Studio.
ILearner interface provides methods and properties that are used to configure and interact with machine learning models. A learner is defined as a set of instructions that perform standardized machine learning tasks. Learners include classification algorithms, clustering algorithms, and regression algorithms.
You can interact with
iLearner only in Studio, or in one of the supported APIs.
Studio uses this interface for the following functionality:
- Determines whether a model has the correct format.
- Gets the capabilities of the learner. These are any general properties of the learner that are not captured by the type signature of the specific learner.
- Gets or sets the settings of the learner.The settings are unique to each learner and must be configured once before any query methods can be called on the learner.
For a list of learners provided by Azure Machine Learning Studio, see Initialize Model.
The ICluster interface is also available, for clustering models only.
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