JKISeason3-18_​ayato

<p><strong>Explaining Cancer Predictions</strong></p><p><strong>Challenge 18</strong></p><p><br><strong>Level: </strong>Hard<br><br><strong>Description: </strong>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 <strong>LIME</strong> and visualization techniques to explain your predictions and make your research more transparent. <strong>Hint:</strong> Learn more about this problem's data attributes <strong>here</strong>.<br><br><strong>Author:</strong> <strong>Keerthan Shetty</strong><br><br><strong>Dataset:</strong> <strong>Breast Tumor Data in the KNIME Community Hub</strong></p>