Support for Machine Learning Studio (classic) will end on 31 August 2024. We recommend you transition to Azure Machine Learning by that date.
Beginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources. Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) resources.
- See information on moving machine learning projects from ML Studio (classic) to Azure Machine Learning.
- Learn more about Azure Machine Learning.
ML Studio (classic) documentation is being retired and may not be updated in the future.
This article describes
IFilter, which is the interface for working with digital signal filters in Machine Learning Studio (classic).
Applies to: Machine Learning Studio (classic) only
Similar drag-and-drop modules are available in Azure Machine Learning designer.
IFilter interface provides methods and properties that are used to configure and interact with digital signal filters that have been defined using one of the filter modules in Studio (classic). For more information, see Filter.
You use the
IFilter interface to save a filter or apply a predefined filter to data.
- Specify a filter to use: its type, coefficients, etc.
- Apply the filter to input data
- Generate a
DataTableof data with filter results
You can interact with
IFilter only in Studio (classic), or in one of the supported APIs.