Understanding Crime and Real Estate Connections
Level: Medium
Description: You ara a data scientist working for a real estate company, and heard a rumour that the "average number of rooms per dwelling" (RM) may be connected to the "per capita crime rate" (CRIM) for different towns. You then decide to investigate if this is the case for Boston, the city where you live and work from. To this end, you decide to experiment with a machine learning regression model and with a topic that you have recently been studying: XAI. How are RM and CRIM connected in Boston? Hint: Consider calculating the SHAP values of each independent feature using a SHAP loop. Hint 2: Consider using a dependence plot (https://hub.knime.com/-/spaces/-/latest/~mMx1llj39or_a-4G/) to verify how RM and CRIM are connected visually.
Dataset Link: https://www.kaggle.com/datasets/funxexcel/boston-housing-dataset-with-column-names
Workflow
Challenge 13 - Understanding Crime and Real Estate Connections
Used extensions & nodes
Created with KNIME Analytics Platform version 5.2.1
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