.. Copyright 2022 Intel Corporation
..
.. Licensed under the Apache License, Version 2.0 (the "License");
.. you may not use this file except in compliance with the License.
.. You may obtain a copy of the License at
..
..     http://www.apache.org/licenses/LICENSE-2.0
..
.. Unless required by applicable law or agreed to in writing, software
.. distributed under the License is distributed on an "AS IS" BASIS,
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.. See the License for the specific language governing permissions and
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########################
Tuning Guide
########################

The performance of some algorithms changes based on the parameters that are used.
This section denotes the details of such cases.

Refer to :ref:`sklearn_algorithms` to see the full list of algorithms, parameters, and data formats supported in |sklearnex|.

.. _acceleration_tsne:

TSNE
----

TSNE algorithm consists of two components: KNN and Gradient Descent.
The overall acceleration of TSNE depends on the acceleration of each of these algorithms.

- The KNN part of the algorithm supports all parameters except:

  - ``metric`` != `'euclidean'` or `'minkowski'` with ``p`` != `2`
- The Gradient Descent part of the algorithm supports all parameters except:

  - ``n_components`` > ``2``
  - ``method`` = ``'exact'``
  - ``verbose`` != ``0``

To get better performance, use parameters supported by both components.