Simple example to make a random forest model with new Python Scrip in KNIME 4.5 using the iris dataset. Saving and reusing the model with Pickle

Simple example to make a random forest model with new Python Scrip in KNIME 4.5 using the iris dataset. Saving and reusing the model with Pickle
Also creating some graphics and exporting them to disk. Via Python code or via KNIME ports. It is not really necessary to do all this with the colourful ports, just to check how it does work

The sub-folder /data/ conatins "py39_knime_2022.yaml" and "py38_knime_2022.yaml" files to create the Python environments if it would not be installed automaticall by the Conda Environment Propagation. Pleas also check out the additional links provided.

External resources

• KNIME and YML configuration with Miniconda (2/2)
• KNIME and YML configuration with Miniconda (1/2)
• KNIME and Jupyter notebooks and .PY modules
• KNIME Python Integration - envconfigs
• envconfigs - KNIME Python Integration (YML files)
• (forum entry) KNIME 4.5 release, problems with conda.environment variable
• use the new (KNIME 4.5) Python Script node to read Parquet file into KNIME, export it again, put it into SQLite database and read it back
• What's New in KNIME Analytics Platform 4.5 - Integrating Python & KNIME
• KNIME columnar storage
• Pandas Tutor visualizes how your Python code transforms dataframes
• (forum.knime.com) RUNNING KNIME USING PYTHON [KNIMEPY]
• Meta Collection about KNIME and Python
• KNIME & Python (the short story)
• Python & KNIME (the official guide)