Table 13.

Activity classification per day over a week duration for P-1 with transfer and incremental learning.

Days	The best performing classifier model(s) used in transfer learning	Actual activity level on day-n	Activity level predicted on day-n after incremental learning	Daily achieved score predicted	Propositional variable
Day-1	DecisionTreeClassifier (criterion = "entropy")	Low Active	Low Active	1	A-2, A-7, A-9
Day-2		Low Active	Low Active	1	A-2, A-7, A-9
Day-3		Medium Active	Medium Active	3	A-4, A-8
Day-4		Active	Active	2	A-3, A-9
Day-5		Low Active	Low Active	1	A-2, A-7, A-9
Day-6		Low Active	Low Active	1	A-2, A-7, A-9
Day-7		Low Active	Low Active	1	A-2, A-7, A-9
Weekly Score	Achieved = ∑Daily_achieved_score_predicted = (1 + 1 + 3 + 2 + 1 + 1 + 1) = 10				–
Prediction accuracy	∑Daily_achieved_score_actual—∑Daily_achieved_score_predicted = 0				–
Difference	Defined_goal_score—Achieved = (21 − 10) = 11				–
Weekly recommendation	Formal message—“You are 11 points behind to reach your weekly goal. Work hard on the following week.” Informal message—“Improve your performance to meet the goal! ☹”				A-11