Counterfactual Explanation (Python)

This KNIME Hub Space is dedicated to example workflows and additional files for the verified component “Counterfactual Explanation (Python)” available here: kni.me/c/wpVF3wtKLnH5V-IR In the folder “01_KNIME_Workflows” you can find the example workflows to explain predictions in KNIME from Keras and scikit-learn models. In the folder “02_Jupyter_Notebooks” you can find Python scripts to train and package models externally. Please note that you can also use KNIME to train models in Python. The file “custom_class_data_processing.py” defines the custom Python class used to normalize the data in training. If you use the “Counterfactual Explanation (Python)” component in a new workflow please add this Python file to the workflow folder via your file system. The data used for training the models was a sample taken from the 1994 Census database available at: archive.ics.uci.edu/ml/datasets/adult

Last edited  Apr 16, 2021 3:23 PM

Data Analytics Job Trends

Last edited  May 11, 2023 10:42 AM

Public

Last edited  Jun 26, 2020 3:28 AM

Trip to KNIME-Python World

This Space contains the workflows used in the presentation "Trip to KNIME Python World" which describes how Low code solutions can be implemented using KNIME and Python.

Last edited  Sep 6, 2022 11:51 AM