a) Which of unsupervised or supervised machine learning is best suited to assessing causation? Explain your choice.

b) Your analytics team presents you with two sets of results that have improved the organizations ability to predict customer defections. The first method uses deep learning and has a precision of 85%. The second method uses decision trees and has a precision of 70%. The previous approach had a precision of 40%.

i) Make a case for using the results of the deep learning method.

ii) Make a case for using the decision tree method.

In your answers, consider aspects of customer lifetime value and managerial decision making.

c) An analytics team used two different models to predict the likelihood of an outcome. The results from two different analysts are below:

Dons Analysis

		Actual
		Positive	Negative
Predicted	Positive	220	100
	Negative	30	650

Katies Analysis

		Actual
		Positive	Negative
Predicted	Positive	170	10
	Negative	80	740

i) Use the Confusion Matrix and Index Calculation tables below to calculate the model performance measures. (15 marks)

Confusion Matrix		Actual
		Positive	Negative
Predicted	Positive	TP	FP
	Negative	FN	TN

	Formula	Don Calculation		Katie Calculation
Accuracy (completed as an example)	(TP + TN) / (TP + TN + FP + FN)	(220 + 650) / (220 + 650 + 100 + 30)	0.87	(170 + 740) / (170 + 740 + 10 + 80)	0.91
Precision	TP / (TP + FP)
Error rate	(FP + FN) / (TP + TN + FP + FN)
Recall	TP / (TP + FN)
Specificity	TN / (TN + FP)
False positive rate	FP / (TN + FP)
F-score	2* ((Precision*Recall) / (Precision + Recall))

ii) Describe a medical or business context where you would prefer to use Dons model. Why do you prefer Dons model?

iii) Describe a medical or business context where you would prefer to use Katies model. Why do you prefer Katies model?

Ian is an intern with the team who claims he made a breakthrough with a model that outperforms both Dons and Katies. The confusion matrix for his model is below:

Ians Analysis

		Actual
		Positive	Negative
Predicted	Positive	249	2
	Negative	1	748

iv) What could possibly have gone wrong that would result in his results being invalid? How could this be solved?