Using an Sklearn Model stored via Pickle and Jupyter Notebook

This example is using a KNIME shared component to load a pickle file (from a Python object serialization library) storing an arbitrary model trained with Python scikit-learn. A python function is loaded from a custom Jupyter Notebook to apply the pickle model on data from KNIME. Both the pickle file and the notebook are saved in this within this workflow. To find them browse in your LOCAL workspace via your file system.

To make this workflow execute you need to:

- Install Anaconda ( anaconda.com/products/individual )
- KNIME Analytics Platform > Preferences > KNIME > Python
- Create new enviroment > name it "jupy_example" or whatever your like.
- Open Anaconda prompt > 'conda install --jupy_example scikit-learn'

External resources

• KNIME and Jupyter - KNIME Blog
• Python Library: scikit-learn
• Python Library: Pickle
• Anaconda Download