This is the Windows app named tsfresh whose latest release can be downloaded as v0.20.0.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named tsfresh with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS
Ad
tsfresh
DESCRIPTION
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
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/tsfresh.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
