Write a python program to cluster candidates into 2/3 groups. The program performs dimensionality reduction, then clustering of candidates based on top 2 PCs. The results are plotted to visually show the performance of candidates. The program performs the following tasks: • Read input "pca cluster.csv" file. Use Panda library. Example of the file: candl cand2 cand3 cand4 cand5 cad6 9. 3 experience education health interview 10 10 8. 10 8 10 4 6. 8. 9. 9. 9 6. 6. 8. test 4 6. 10 9. communication skills 6. 9. 10 10 writing skills team player 10 6. 6. 8. 7 4 10 9. 2. leadership enthusiasm ready to start flexible in hours able to relocate references 4 10 4 8 7 7 9. 6. 9 10 6. 7. 6. 6. 6 10 4 10 9. 4. • Apply PCA analysis to identify top 2 PCs. Eigen No. 0 Eigen value- (33.50+0j) Contribution % (40.87+0j) Points on new seale [5 5-8 30-5] Eigen No. 1 Eigen value (22.65+0j) Contribution % (27.63+0j) Points on new scale [0-4107-5] • Calculate the scores on top 2 PCs: PCI [5 5-8 3 0-5] PC2 | 0 -4 107-5j • Apply K-Means cluster algorithm to classify candidates into 2 clusters. Plot the results as shown (see below plot) • Repeat clustering and plot for K-3 (see below plot) • Finally, present discussion paragraph (about % page) to answer the following point: "If you are a hiring manger, how the this analysis help you to choose/narrow candidates"
Write a python program to cluster candidates into 2/3 groups. The program performs dimensionality reduction, then clustering of candidates based on top 2 PCs. The results are plotted to visually show the performance of candidates. The program performs the following tasks: • Read input "pca cluster.csv" file. Use Panda library. Example of the file: candl cand2 cand3 cand4 cand5 cad6 9. 3 experience education health interview 10 10 8. 10 8 10 4 6. 8. 9. 9. 9 6. 6. 8. test 4 6. 10 9. communication skills 6. 9. 10 10 writing skills team player 10 6. 6. 8. 7 4 10 9. 2. leadership enthusiasm ready to start flexible in hours able to relocate references 4 10 4 8 7 7 9. 6. 9 10 6. 7. 6. 6. 6 10 4 10 9. 4. • Apply PCA analysis to identify top 2 PCs. Eigen No. 0 Eigen value- (33.50+0j) Contribution % (40.87+0j) Points on new seale [5 5-8 30-5] Eigen No. 1 Eigen value (22.65+0j) Contribution % (27.63+0j) Points on new scale [0-4107-5] • Calculate the scores on top 2 PCs: PCI [5 5-8 3 0-5] PC2 | 0 -4 107-5j • Apply K-Means cluster algorithm to classify candidates into 2 clusters. Plot the results as shown (see below plot) • Repeat clustering and plot for K-3 (see below plot) • Finally, present discussion paragraph (about % page) to answer the following point: "If you are a hiring manger, how the this analysis help you to choose/narrow candidates"
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
Related questions
Question
![l JO 100 4G
2:02 AM
@ 52%
assignment_3 v2
AI and ML
Assignment 3
Write a python program to cluster candidates into 2/3 groups. The program performs
dimensionality reduction, then clustering of candidates based on top 2 PCs. The results are
plotted to visually show the performance of candidates.
The program performs the following tasks:
Read input "pca cluster.csv" file. Use Panda library. Example of the file:
candi
cand2
cand3
cand4
cand5
cad6
experience
10
9
7
3
education
10
10
8
10
health
4
6
8
9
9.
interview
9
6
6
8
7
test
4
9.
10
communication skills
7.
6
9
10
10
writing skills
team player
leadership
10
9
6
6.
8
7
4
10
9
4
10
4
9
6
8
5
9
7
enthusiasm
7.
7
7
9
ready to start
5
6
6.
9
1
flexible in hours
10
1
9.
5
6.
able to relocate
6
6
6.
10
4
references
9
9
7
9
4
10
• Apply PCA analysis to identify top 2 PCs.
Eigen No. 0 Eigen value (33.50+0j) Contribution % (40.87+0j)
Points on new scale [5 5-8 3 0-5]
Eigen No. I Eigen value- (22.65+Oj) Contribution % (27.63+0j)
Points on new scale [0-4107-5]
• Calculate the scores on top 2 PCs:
PCI [5 5-8 3 0 -5]
PC2 |0-4 10 7-5
• Apply K-Means cluster algorithm to classify candidates into 2 clusters. Plot the results as
shown (see below plot)
• Repeat clustering and plot for K=3 (see below plot)
• Finally, present discussion paragraph (about ½ page) to answer the following point: "If
you are a hiring manger, how the this analysis help you to choose/narrow candidates"
j
Clusters
Cand 5](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F6da1d9a4-4e5d-43b1-b872-c946b5f04dde%2F90767795-bdc6-429d-932f-ff901f5ccc1d%2F42hwp0a_processed.jpeg&w=3840&q=75)
Transcribed Image Text:l JO 100 4G
2:02 AM
@ 52%
assignment_3 v2
AI and ML
Assignment 3
Write a python program to cluster candidates into 2/3 groups. The program performs
dimensionality reduction, then clustering of candidates based on top 2 PCs. The results are
plotted to visually show the performance of candidates.
The program performs the following tasks:
Read input "pca cluster.csv" file. Use Panda library. Example of the file:
candi
cand2
cand3
cand4
cand5
cad6
experience
10
9
7
3
education
10
10
8
10
health
4
6
8
9
9.
interview
9
6
6
8
7
test
4
9.
10
communication skills
7.
6
9
10
10
writing skills
team player
leadership
10
9
6
6.
8
7
4
10
9
4
10
4
9
6
8
5
9
7
enthusiasm
7.
7
7
9
ready to start
5
6
6.
9
1
flexible in hours
10
1
9.
5
6.
able to relocate
6
6
6.
10
4
references
9
9
7
9
4
10
• Apply PCA analysis to identify top 2 PCs.
Eigen No. 0 Eigen value (33.50+0j) Contribution % (40.87+0j)
Points on new scale [5 5-8 3 0-5]
Eigen No. I Eigen value- (22.65+Oj) Contribution % (27.63+0j)
Points on new scale [0-4107-5]
• Calculate the scores on top 2 PCs:
PCI [5 5-8 3 0 -5]
PC2 |0-4 10 7-5
• Apply K-Means cluster algorithm to classify candidates into 2 clusters. Plot the results as
shown (see below plot)
• Repeat clustering and plot for K=3 (see below plot)
• Finally, present discussion paragraph (about ½ page) to answer the following point: "If
you are a hiring manger, how the this analysis help you to choose/narrow candidates"
j
Clusters
Cand 5
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by step
Solved in 4 steps with 6 images
Recommended textbooks for you
Computer Networking: A Top-Down Approach (7th Edi…
Computer Engineering
ISBN:
9780133594140
Author:
James Kurose, Keith Ross
Publisher:
PEARSON
Computer Organization and Design MIPS Edition, Fi…
Computer Engineering
ISBN:
9780124077263
Author:
David A. Patterson, John L. Hennessy
Publisher:
Elsevier Science
Network+ Guide to Networks (MindTap Course List)
Computer Engineering
ISBN:
9781337569330
Author:
Jill West, Tamara Dean, Jean Andrews
Publisher:
Cengage Learning
Computer Networking: A Top-Down Approach (7th Edi…
Computer Engineering
ISBN:
9780133594140
Author:
James Kurose, Keith Ross
Publisher:
PEARSON
Computer Organization and Design MIPS Edition, Fi…
Computer Engineering
ISBN:
9780124077263
Author:
David A. Patterson, John L. Hennessy
Publisher:
Elsevier Science
Network+ Guide to Networks (MindTap Course List)
Computer Engineering
ISBN:
9781337569330
Author:
Jill West, Tamara Dean, Jean Andrews
Publisher:
Cengage Learning
Concepts of Database Management
Computer Engineering
ISBN:
9781337093422
Author:
Joy L. Starks, Philip J. Pratt, Mary Z. Last
Publisher:
Cengage Learning
Prelude to Programming
Computer Engineering
ISBN:
9780133750423
Author:
VENIT, Stewart
Publisher:
Pearson Education
Sc Business Data Communications and Networking, T…
Computer Engineering
ISBN:
9781119368830
Author:
FITZGERALD
Publisher:
WILEY