An ML Pipeline to be executed by 'mlpiper' tool
This is an example of a machine-learning pipeline that is implemented by the 'mlpiper' platform.
This specific example is no more than a simple sklearn implementation, without using the built-in sklearn Pipeline structure.
The pipeline description is provided by the
Download the tarball source code and extract it
Open a terminal and change directory to the extracted folder
Create virtual env, whose name is 'mlpiper', or anything else (If you've already created it, use
workonto activate it):
> mkvirtualenv --python=3 mlpiper
Install the requirements (Skip if already installed):
> pip install -r requirements.txt
(Note: Please make sure the environment was setup properly. Refer to 'Setup' section above for more information)
Browse to the extracted folder
... Log Loss: 0.6571923425816221 ROC AUC Score: 0.6350086940964011 ... real 0m2.199s user 0m2.528s sys 0m0.295s
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