Assignment 13- Comparing Classifiers using Confusion Matrices
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Assignment 13: Comparing Classifiers using Confusion Matrices
Prasad Srinivas
IFT 511: Analyzing Big Data
Professor: Asmaa Elbadrawy
Tuesday and Thursday (12:00 PM – 1:15 PM)
November 4, 2023
Confusion Matrix
1.
What is the overall accuracy?
Overall Accuracy:
= (True Positives + True Negatives) / Total Data Points
= (650 + 100) / 650+50+200+100
= 750 / 1000
= 0.75 = 75%
2.
What is the accuracy over the +ve class?
Accuracy over the class:
= Tp/ Tp+fn
= 650 / 700
= 0.9286 = 92.86%
3.
What is the accuracy over the -ve class?
Accuracy over the -ve class:
= Tn / Tn + fp
= 100 / 300
= 0.3333 =33.33%
4.
What is the True Positive Rate (TPR)?
True Positive Rate (TPR):
= Tp / Tp + fn
TPR = 650 / 700
TPR = 0.9286 TPR = 92.86%
5.
What is the True Negative Rate (TNR)?
True Negative Rate (TNR):
TNR = Tn/Tn+Fp
TNR = 100 / 300
TNR = 0.3333 TNR=33.33%
6.
What is the Recall?
Recall = True Positives / Total Data Points
Recall = 650 / 700
Recall = 0.9286 or 92.86%
7.
What is the Precision?
Precision = Tp/Tp+Fp
Precision = 650 / (650 + 200)
Precision = 650 / 850
Precision = 0.7647 Precision = 76.47%
8.
What is the F-measure?
F-measure = 2 * (Precision * Recall) / (Precision + Recall)
F-measure = 2 * (0.7647 * 0.9285) / (0.7647 + 0.9285)
F-measure = 0.8386
Expected Value
Expected value: P(Tp) *B(Tp)+P(Fp)*B(Fp)+P(Fn)*B(Fn)+P(Tn)*B(Tn)
=650/1000*(2) +200/1000* (-1) +50/1000(-3)+100/1000(0)
=95/100
=0.95
Expected Value = $950
Comparing Classifiers
1.
What is the overall accuracy given by M2?
Overall Accuracy is given by M2:
= (True Positives + True Negatives) / Total Data Points
= (550 + 200) / (550 + 100 + 150 + 200)
= 750 / 1000
= 0.75 or 75%
2.
What is the accuracy over the +ve class given by M2?
Accuracy over the +ve class:
=Tp/(Tp+Fn)
= 550 / (550 + 150)
= 550 / 700
= 0.7857 or 78.57%
3.
What is the accuracy over the -ve class given by M2?
Accuracy over the -ve class:
= Tn / Tn +Fp
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= 200 / (100 + 200)
= 200 / 300
= 0.6667 or 66.67%
4.
How does M1 compare to M2 in terms of their accuracy on the +ve & -ve classes?
The accuracy of M1 was better than M2 over +ve class
The accuracy of M2 was better than M1 over -ve class.
5.
If the goal is to build a model that gives the highest possible accuracy over the -ve class, which model
do you think works best in that regard?
The M2 model works best in the given scenario.
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Assignment 2: (CLO 5): MS Excel application:
Determine any four related variables, two of them are qualitative (Categorical)
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a. Input sufficient data about the four variables (a random sample of 50 or more)
in MS-Excel sheet.
b. Prepare frequency distribution tables for one qualitative and one quantitative
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c. Prepare appropriate graphs for each of the two tables.
d. Prepare a pivot table (cross tabulation) consists of two qualitative variables (in
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You pick a random letter from the alphabet, draw a marble from a bag of 6 mar-
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2. ARITHMETIC GEOMETRIC CURVE
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Nate: answer on a separate document. Use excel in compute.
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Supposed this is Yc
(straightline)
450,000
370,000
750,000
1,100,000
1,500,000
1,000,000
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Yi + 1
(Geometric)
YEAR
SALES
415,000 1
356,000
703,556
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1,308,905
900,573
1,504,789
1,705,932
1,895,890
2,094,256
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2012
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2015
2016
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2017
2018
8
2019
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