10 pts Select only one method. Fit your model. Feel free to adjust parameters or try a grid search (optional)
10 pts Return the accuracy score of the train set and test set (suggestion to use .score()). Print the confusion matrix and classification report of the test set.
10 pts Discuss the precision score for class 8. Support this with your visual opinion from plots in 1D as well as the confusion matrix.
10 pts Discuss the recall score for class 5. Support this with your visual opinion from plots in 1D as well as the confusion matrix.
10 pts Which metric do you feel is the most important in the following business case: You work for ComEd, a local electricity supplier. You head a department that uses analytics to plan electrical supply for Chicago’s power grid. Assume that your department budgets for a certain amount of electrical supply at a fixed low rate. If the total demand in Chicago stays within the purchased supply levels, your department is performing. If the demand breaches this supply level, the company is penalized and the rate for your supply multiplies by 100x, destroying your department’s performance. If you had to build your forecast model to classify patterns of high electrical usage (appliances, air conditioning, water heating) vs low electrical usage (lighting, tv, phone chargers) which metric (precision or recall) would you use
