For numbers 2-7: A remission is when leukemia cannot be detected in the body and there are no symptoms. A total of 27 random sample of patients from a certain hospital was obtained. The Leukemia Remission data set has a response variable of whether leukemia remission occurred (Y=1). The predictor variables are cellularity of the marrow clot section (CELL) and proportion of absolute marrow leukemia cell infiltrate (INFIL). Regression analysis was done and the model is given by: π(y=1) In = = -2.88 +3.08CELL - 2.5INFIL L1-π(y=1)] Macbee wants to validate the model above. He observed 30 random sample of patients from the same hospital. He came up with a confusion matrix below. Predicted Probability Outcome < 0.5 > 0.5 0 (with parasite) 5 2 1 (without parasite) 1 20 5. The accuracy of MacBee's model is _______%. O A. 17.9 O B.21.4 O C. 71.4 O D. 89.3
For numbers 2-7: A remission is when leukemia cannot be detected in the body and there are no symptoms. A total of 27 random sample of patients from a certain hospital was obtained. The Leukemia Remission data set has a response variable of whether leukemia remission occurred (Y=1). The predictor variables are cellularity of the marrow clot section (CELL) and proportion of absolute marrow leukemia cell infiltrate (INFIL). Regression analysis was done and the model is given by: π(y=1) In = = -2.88 +3.08CELL - 2.5INFIL L1-π(y=1)] Macbee wants to validate the model above. He observed 30 random sample of patients from the same hospital. He came up with a confusion matrix below. Predicted Probability Outcome < 0.5 > 0.5 0 (with parasite) 5 2 1 (without parasite) 1 20 5. The accuracy of MacBee's model is _______%. O A. 17.9 O B.21.4 O C. 71.4 O D. 89.3
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![For numbers 2-7: A remission is when leukemia cannot be detected in the body and there are no symptoms. A total of 27 random sample of patients from a certain
hospital was obtained. The Leukemia Remission data set has a response variable of whether leukemia remission occurred (Y=1). The predictor variables are cellularity
of the marrow clot section (CELL) and proportion of absolute marrow leukemia cell infiltrate (INFIL). Regression analysis was done and the model is given by:
π(y=1)
= -2.88 +3.08CELL - 2.5INFIL
In\1-7(y=1)] =
Macbee wants to validate the model above. He observed 30 random sample of patients from the same hospital. He came up with a confusion matrix below.
Predicted Probability
Outcome
< 0.5
> 0.5
0 (with parasite)
5
2
1 (without parasite)
1
20
5. The accuracy of MacBee's model is
O A. 17.9
OB. 21.4
O C. 71.4
O D. 89.3
%.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3478eb2b-d575-460e-8941-9efa289dcb01%2F2a3df24e-2597-4cc8-a646-25e717c6c29e%2F5mwn9ve_processed.jpeg&w=3840&q=75)
Transcribed Image Text:For numbers 2-7: A remission is when leukemia cannot be detected in the body and there are no symptoms. A total of 27 random sample of patients from a certain
hospital was obtained. The Leukemia Remission data set has a response variable of whether leukemia remission occurred (Y=1). The predictor variables are cellularity
of the marrow clot section (CELL) and proportion of absolute marrow leukemia cell infiltrate (INFIL). Regression analysis was done and the model is given by:
π(y=1)
= -2.88 +3.08CELL - 2.5INFIL
In\1-7(y=1)] =
Macbee wants to validate the model above. He observed 30 random sample of patients from the same hospital. He came up with a confusion matrix below.
Predicted Probability
Outcome
< 0.5
> 0.5
0 (with parasite)
5
2
1 (without parasite)
1
20
5. The accuracy of MacBee's model is
O A. 17.9
OB. 21.4
O C. 71.4
O D. 89.3
%.
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