Explaining Cancer Predictions
Challenge 18
Level: Hard
Description: You work as a researcher creating models to identify whether a breast tumor is benign or malign, based on anonymized patient data. Besides obtaining a classifier that works very well for both benign and malign cases, you must be able to explain how different feature values impact your results. Experiment with LIME and visualization techniques to explain your predictions and make your research more transparent. Hint: Learn more about this problem's data attributes here.
Author: Keerthan Shetty
Dataset: Breast Tumor Data in the KNIME Community Hub