This is the Windows app named AutoMLPipeline.jl whose latest release can be downloaded as v0.4.7sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named AutoMLPipeline.jl 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
AutoMLPipeline.jl
DESCRIPTION
AutoMLPipeline (AMLP) is a package that makes it trivial to create complex ML pipeline structures using simple expressions. It leverages on the built-in macro programming features of Julia to symbolically process, and manipulate pipeline expressions and makes it easy to discover optimal structures for machine learning regression and classification. To illustrate, here is a pipeline expression and evaluation of a typical machine learning workflow that extracts numerical features (numf) for ica (Independent Component Analysis) and pca (Principal Component Analysis) transformations, respectively, concatenated with the hot-bit encoding (ohe) of categorical features (catf) of a given data for rf (Random Forest) modeling.
Features
- Symbolic pipeline API for easy expression and high-level description of complex pipeline structures and processing workflow
- Common API wrappers for ML libs including Scikitlearn, DecisionTree, etc
- Easily extensible architecture by overloading just two main interfaces: fit! and transform
- Meta-ensembles that allow composition of ensembles of ensembles (recursively if needed) for robust prediction routines
- Categorical and numerical feature selectors for specialized preprocessing routines based on types
- AutoMLPipeline is in the Julia Official package registry
Programming Language
Julia
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/automlpipeline-jl.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
