2.1 You are required to evaluate the performance of the selected algorithms from Question 1 by using
the following assumptions in your computation: (15)
ALGORITHM 1
True Positive = 65
True Negative = 70
False Positive = 80
False Negative = 90
ALGORITHM 2
True Positive = 75
True Negative = 80
False Positive = 40
False Negative = 45
Compute the following Machine Learning metrics by showing your working:
Accuracy
Precision
Recall
F1-Measure
2.2 Compare the performance of the selected algorithms from Question 1 based on the Accuracy and
Precision values. (5)
2.3 Contrast the performance of the selected algorithms based on the Recall and F1- Measure. (5)
ALGORITHM 1
i. Accuracy
Accuracy=correct predictions/total prediction
=(65+70)/(65+80+90+70)
=135/305
=0.442623
ii. Precision
precision=TP/(TP+FP)
=65/(65+80)=65/145
=0.448276
iii. Recall
recall=TP/(TP+FN)
=65/(65+90)
=65/155
=0.4193548
ALGORITHM 2
i. Accuracy
Accuracy=correct predictions/total prediction
=(75+80)/(75+45+40+80)
=155/240
=0.64583
ii. Precision
precision=TP/(TP+FP)
=75/(75+45)
=75/120
=0.625
iii. Recall
recall=TP/(TP+FN)
=75/(75+40)
=75/115
=0.652173
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