Supported input types

Just like Scikit-Learn estimators, estimators from Intel(R)’s Extension are able to accept and work with different classes of input data, including:

• Numpy arrays.

• Other array classes implementing the Array API protocol (see Array API support for details).

• SciPy sparse arrays and sparse matrices (depending on the estimator).

• Pandas DataFrame and Series classes.

In addition, Intel(R)’s Extension also supports:

• dpnp arrays.

• dpctl arrays.

Stock Scikit-Learn estimators, depending on the version, might offer support for additional input types beyond this list, such as DataFrame and Series classes from other libraries like Polars.

Intel(R)’s Extension currently does not offer accelerated routines for input types not listed here - when receiving an unsupported class, estimators will fall back to stock Scikit-Learn to handle it, so make sure to convert them to a supported type when using Intel(R)’s Extension.