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tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python. The extracted features can be used to describe or cluster time series based on the extracted characteristics. Further, they can be used to build models that perform classification/regression tasks on the time series. Often the features give new insights into time series and their dynamics.
Features
- Used for the prediction of the life span of machines
- Used for the prediction of the quality of steel billets during a continuous casting process
- Time Series Feature extraction based on scalable hypothesis tests
- Automatically extracts 100s of features from time series
- It frees your time spent on building features by extracting them automatically
- Contains many feature extraction methods and a robust feature selection algorithm
Project Samples
