(O4) Helping tags: Statistics, Analysis of Relationships Among Variables, Logistic Regression Analysis, Linear Discriminant Analysis......WILL UPVOTE, just pls help me answer the following questions in the attached image. Pls show complete solutions and explain them. Thank you! 4. Cancer is a disease caused by abnormal growth and proliferation of cellsin the body. A model is constructed to predict whether a cancer ismalignant (1) or benign (0) using uniformity in cell size (X1, score from 1to 10) and uniformity in cell shape (X2, score from 1 to 10). The biopsyresults of two hundred randomly selected patients from a certain hospitalwere used to construct the following model:π(y=1)In[((-²)] = −5.07 +0.60X₁ +0.79X₂[1¬n(y=1)]The confusion matrix for the constructed model is shown below:Outcome0 (benign)1 (malignant)The accuracy of the model isA. 7.0B. 62.0C. 91.8D. 93.0_%.Predicted Probability< 0.5> 0.51305956

Answered: Image /qna-images/answer/92982524-8a00-44b2-a360-015cc3a7f307.jpg

Answered: The accuracy of the model is _%.

Math

Statistics

The accuracy of the model is _%.

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter2: Systems Of Linear Equations

Section2.4: Applications

Problem 2EQ: 2. Suppose that in Example 2.27, 400 units of food A, 500 units of B, and 600 units of C are placed...

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(O4) Helping tags: Statistics, Analysis of Relationships Among Variables, Logistic Regression Analysis, Linear Discriminant Analysis

WILL UPVOTE, just pls help me answer the following questions in the attached image. Pls show complete solutions and explain them. Thank you!

4. Cancer is a disease caused by abnormal growth and proliferation of cells
in the body. A model is constructed to predict whether a cancer is
malignant (1) or benign (0) using uniformity in cell size (X1, score from 1
to 10) and uniformity in cell shape (X2, score from 1 to 10). The biopsy
results of two hundred randomly selected patients from a certain hospital
were used to construct the following model:
π(y=1)
In[((-²)] = −5.07 +0.60X₁ +0.79X₂
[1¬n(y=1)]
The confusion matrix for the constructed model is shown below:
Outcome
0 (benign)
1 (malignant)
The accuracy of the model is
A. 7.0
B. 62.0
C. 91.8
D. 93.0
_%.
Predicted Probability
< 0.5
> 0.5
130
5
9
56

Definition Definition Statistical method that estimates the relationship between a dependent variable and one or more independent variables. In regression analysis, dependent variables are called outcome variables and independent variables are called predictors.

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