00:01
So to solve this problem first we need to draw a table.
00:06
So we draw a table of size, two column and 11 rows.
00:22
The column is actual class and predicted class.
00:43
So the first is 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.
01:02
1 1 1 1 1 1 1 1 1 0 0 1 1 1 0 1 so since we need to take 0 .5 as the cutoff value so the predicted probabilities are let's take a quick look through two examples of how this is calculated for the class for the first of the probability that the predicted class will be 1 is 0 .09 which is less than 0 .5 thus its predicted class is 0 .7 for third observation the probability that the predicted class will be 1 is 0 .77 which is for the third observation which is greater than 0 .5 so predicted class is 1 so we can calculate misclassification rate equal to there are 2 classes so 2 by 10 that is equal to 0 .10 that is equal to 0.
03:12
So this is the first answer.
03:26
The second is the number of classes correctly classified relative to the total number of classes in the accuracy rate.
03:39
So accuracy rate is 8 by 10.
03:46
That is equal to 0 .8.
03:55
So the answer is 0 .8...