Suppose you build a classifier on a given data set with two classes, namely positive and negative and the classifier outputs the results in the form of confusion matrix as shown in Table 1. Table 1: Confusion Matrix Predictions + Actual + 80 230 (a) Fill in the following values based on the given questions (i) True Positive: (ii) True Negative: (iii) False Positive: (iv) False Negative: (b) Calculate the accuracy obtained from the classifier. Show the computation to obtain the accuracy rate. (c) Calculate the precision obtained from the classifier. Show the computation to obtain the precision rate. (d) Calculate the recall obtained from the classifier. Show the computation to obtain the recall rate. 70 840
Suppose you build a classifier on a given data set with two classes, namely positive and negative and the classifier outputs the results in the form of confusion matrix as shown in Table 1. Table 1: Confusion Matrix Predictions + Actual + 80 230 (a) Fill in the following values based on the given questions (i) True Positive: (ii) True Negative: (iii) False Positive: (iv) False Negative: (b) Calculate the accuracy obtained from the classifier. Show the computation to obtain the accuracy rate. (c) Calculate the precision obtained from the classifier. Show the computation to obtain the precision rate. (d) Calculate the recall obtained from the classifier. Show the computation to obtain the recall rate. 70 840
C++ Programming: From Problem Analysis to Program Design
8th Edition
ISBN:9781337102087
Author:D. S. Malik
Publisher:D. S. Malik
Chapter10: Classes And Data Abstraction
Section: Chapter Questions
Problem 10SA:
Consider the definition of the class product Type as given in Exercise 8.
Answer the following...
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Question
a and b please, and if possible to do c and d too
![Suppose you build a classifier on a given data set with two classes, namely positive and
negative and the classifier outputs the results in the form of confusion matrix as shown in
Table 1.
Table 1: Confusion Matrix
+
Actual
+
80
230
(a) Fill in the following values based on the given questions
(i) True Positive:
(ii) True Negative:
(iii) False Positive:
(iv) False Negative:
(b) Calculate the accuracy obtained from the classifier. Show the computation to obtain the
accuracy rate.
(c) Calculate the precision obtained from the classifier. Show the computation to obtain the
precision rate.
(d) Calculate the recall obtained from the classifier. Show the computation to obtain the
recall rate.
Predictions
-
70
840](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4bf9c5f1-b2c9-4d91-952f-63497f8b9557%2Fe15ac9be-3e98-4b23-847f-10a9e2ee2780%2Fdh0h2ya_processed.png&w=3840&q=75)
Transcribed Image Text:Suppose you build a classifier on a given data set with two classes, namely positive and
negative and the classifier outputs the results in the form of confusion matrix as shown in
Table 1.
Table 1: Confusion Matrix
+
Actual
+
80
230
(a) Fill in the following values based on the given questions
(i) True Positive:
(ii) True Negative:
(iii) False Positive:
(iv) False Negative:
(b) Calculate the accuracy obtained from the classifier. Show the computation to obtain the
accuracy rate.
(c) Calculate the precision obtained from the classifier. Show the computation to obtain the
precision rate.
(d) Calculate the recall obtained from the classifier. Show the computation to obtain the
recall rate.
Predictions
-
70
840
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