A 1 what percentage of the total cases in the validation set...

Name: a 1 what percentage of the total cases in the validation set are correctly classified note do not round intermediate calculations and round final answer to 2 decimal places a 2 what percenta 18615
Uploaded: 2022-05-06T16:13:50-08:00
Duration: 5 min 48 s
Channel: Shaiju T
Description: a 1 what percentage of the total cases in the validation set are correctly classified note do not round intermediate calculations and round final answer to 2 decimal places a 2 what percenta 18615

a-1. What percentage of the total cases in the validation set are correctly classified? Note: Do not round intermediate calculations and round final answer to 2 decimal places. a-2. What percentage of the target class cases (y = 1) in the validation set are correctly classified? Note: Do not round intermediate calculations and round final answer to 2 decimal places. a-3.What percentage of the nontarget class cases (y= 0) in the validation set are correctly classified? Note: Do not round intermediate calculations and round final answer to 2 decimal places.

Transcript

00:01 Hey everyone in this video, the prediction class is 1 if predicted probability is greater than and equal to 0 .5, otherwise the prediction class is equal to 0.

00:13 So prediction class is 1 if predicted probability is greater than or equal to 0 .5, otherwise prediction class is equal to 0.

00:22 So now the confusion matrix is as follows.

00:27 So now the confusion matrix is shown in the table where we have actual class from 1 to 0 and we have predicted class that is also from 1 to 0 and we have tp, fp, fn and tn.

00:45 So in the confusion matrix we have actual class from 1 and 0 and predicted class that is also 1 and 0 and the value of tp is 4 and the value of fp is 1 and the value of fn is equal to 2 and tn is equal to 3.

01:05 So this is the confusion matrix.

01:08 So now we will study that what is fp, tp, fn and tn.

01:14 So now true positive that is tp.

01:17 Tp is true positive.

01:19 It means the actual label is 1 and the predicted label is also 1.

01:25 So tp is true positive which means the actual label is 1 and the predicted label is also 1.

01:38 Now the tn whose value is 3 in predicted and actual class as shown in the 3.

01:45 Confusion matrix tn is true negative which means the actual label is 0 and the predicted label is also 0 the tn whose value is 3 which is shown in the confusion matrix in the actual class and predicted class is true negative it means the actual label is 0 and the predicted label is also 0 see we have true positive that is tp and true negative that is tn.

02:16 Tp or true positive means the actual label is one and the predicted label is also one and the true n that is tn that means the actual level is zero and the predicted label is also zero.

02:31 Now next we have fp and whose value is one in the confusion matrix and fp means false positive.

02:40 Fp means false positive and it means the actual label is 0 and the predicted label is 1.

02:48 Fp, that is false positive, means that the actual label is 0 and the predicted label is 1...

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