Finally, assume you want to compare the k-NN model above aga…
Finally, assume you want to compare the k-NN model above against a Regression Tree model (not shown) which you train on the same data. You obtain the following error metrics for the regression tree: Metric Regression Tree Mean Error (ME) 1.2 Root Mean Square Error (RMSE) 5.43 Compare the ME and RMSE obtained above for the k-NN model to the ME and RMSE of the Regression Tree. You need to decide which model you would recommend your company use. In making your choice, assume that the listing price of a house cannot be increased after it is set. If the listing price is too high, buyers can try to negotiate a lower price. But if the listing price turns out to be low, the seller cannot increase it.