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sktime seeks to provide a unified framework for multiple time series machine learning tasks. This (hopefully) makes sktime's functionality intuitive for users and lets developers extend the framework more easily. But time series data and the related scientific use cases each can take multiple forms.
- Installation
To develop sktime locally, or to contribute to the project,...
- Time series classification
The sktime.classification module contains algorithms and...
- Installation
Current local time in Slovakia – Bratislava. Get Bratislava's weather and area codes, time zone and DST. Explore Bratislava's sunrise and sunset, moonrise and moonset.
sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes forecasting, time series classification, clustering, anomaly/changepoint detection, and other tasks.
Slovakia time zone and map with current time in the largest cities.
To develop sktime locally, or to contribute to the project, you need to set up: a local clone of the sktime repository. a virtual environment with an editable install of sktime and its developer dependencies. The following steps guide you through the process: 2. Set up a new virtual environment.
The sktime.classification module contains algorithms and composition tools for time series classification. All classifiers in sktime can be listed using the sktime.registry.all_estimators utility, using estimator_types="classifier" , optionally filtered by tags.
This tutorial is about sktime - a unified framework for machine learning with time series. sktime features various time series algorithms and modular tools for sktime is a widely used scikit-learn compatible library for learning with time series.
