Get Started#
The following information is designed to get users up and running with
skbase quickly. For more detailed information, see the links in each
of the subsections.
Installation#
skbase currently supports:
environments with python version 3.8, 3.9, 3.10, 3.11 or 3.12
operating systems Mac OS X, Unix-like OS, Windows 8.1 and higher
installation via
PyPi
Users can choose whether to install the skbase with its standard dependencies or
alternatively to install skbase with all its dependencies using the
code snippets below.
pip install scikit-base
pip install scikit-base[all_extras]
Note
We are still working on creating releases of skbase on conda.
If you would like to help, please open a pull request.
Note
We are still working on creating releases of skbase on conda.
If you would like to help, please open a pull request.
For additional details see our full installation guide.
Key Concepts#
skbase seeks to provide a general framework for creating and
working with classes that follow scikit-learn, and sktime style design patterns.
Primary functionality is provided through base classes that provide interfaces for:
scikit-learn style parameter getting and setting
using tags to record characteristics of the class that can be used to alter the classes code or how it interacts with other functionality
generating test instances
To make it easy to build toolboxes and
applications that use skbase’s, interfaces
are also provided for:
retrieving information on
BaseObject-sautomating the testing of
BaseObject-svalidating
BaseObject-s or collections ofBaseObjects-s
Warning
The skbase package is new and its interfaces are still experimental. The
package’s API may change as each functional area reaches maturity.
Quickstart#
The code snippets below are designed to introduce skbase’s
functionality. For more detailed information see the Tutorials,
User Guide and API Reference in skbase’s
Documentation.