Gujarat Technological UniversityWinter 2024 examination

GTU 3160714 Data Mining Winter 2024 Question Paper & PDF

B.E. · Computer Engineering · Semester 6 · Subject code 3160714
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Total
70 marks
To pass
23 marks (33%)
Duration
2.5 Hours 2:30 PM – 5:00 PM
Questions
5 with internal choice
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11 of 25 questions on this paper were also asked in other years. 1 more is a type of question GTU sets again with new data. Each is marked below with the years it appeared.See all 27 repeated 3160714 questions, most asked first

Q.1

14 Marks
(a)
3 marks

Define each of the following data mining functionalities: characterization, discrimination, regression.

(b)
4 marks
How is a data warehouse different from database?
(c)
7 marksAsked in 7 of 7 papers
Explain KDD process.

Also asked in Summer 2026 Q1c, Winter 2025 Q2c, Summer 2025 Q1b, Summer 2024 Q1b, Winter 2023 Q1c, Summer 2023 Q1c

Q.2

14 Marks
(a)
3 marksAsked in 4 of 7 papers
How to handle missing values? Explain.

Also asked in Summer 2025 Q2b, Summer 2024 Q2c, Summer 2023 Q1b

(b)
4 marksAsked in 2 of 7 papers
How to handle noisy data?

Also asked in Summer 2024 Q2a

(c)
7 marksSame type asked in 3 of 7 papers

Consider a database, D, consisting of 9 transactions. Suppose min. support count required is 2. Let minimum confidence required is 70%. Find out the frequent itemset using Apriori algorithm.

Also asked in Winter 2023 Q2c OR, Summer 2023 Q2c OR

(c)
7 marks

A database has five transactions. Let min sup=60% and min conf =80%. Tid Item brought T100 T200 T300 T400 T500 {M, O, N, K, E, Y} {D, O, N, K, E, Y} {M, A, K, E} {M, U, C, K, Y} {C, O, O, K, I, E} Find all frequent item sets using Apriori and FP-growth, respectively. Compare the efficiency of the two mining processes.

Q.3

14 Marks
(a)
3 marks
Explain market basket analysis.
(b)
4 marksAsked in 2 of 7 papers
Explain Linear regression.

Also asked in Winter 2023 Q3b OR

(c)
7 marksAsked in 5 of 7 papers
Explain decision tree algorithm.

Also asked in Winter 2025 Q3c, Summer 2025 Q4c, Summer 2024 Q4c, Winter 2023 Q3c

(a)
3 marks
Explain WEKA tool.
(b)
4 marks
Explain logistic regression.
(c)
7 marks
Explain CART Classification Method.

Q.4

14 Marks
(a)
3 marksAsked in 3 of 7 papers
Compare classification and Clustering.

Also asked in Winter 2025 Q5b, Summer 2023 Q4a

(b)
4 marks
Which metrics used for evaluating classifier performance?
(c)
7 marks
Explain Principal Component Analysis.
(a)
3 marksAsked in 3 of 7 papers
Compare classification and prediction.

Also asked in Winter 2025 Q3a OR, Winter 2023 Q3b

(b)
4 marksAsked in 4 of 7 papers
Explain outlier detection.

Also asked in Winter 2025 Q5a, Summer 2025 Q5b, Summer 2023 Q3a OR

(c)
7 marksAsked in 2 of 7 papers
Explain Backpropagation algorithm.

Also asked in Summer 2024 Q4b

Q.5

14 Marks
(a)
3 marks
Write applications of clustering graph and network data.
(b)
4 marks
What is Web log structure? And discuss issues regarding web logs.
(c)
7 marksAsked in 2 of 7 papers
Explain PAM clustering Algorithm.

Also asked in Winter 2025 Q5c OR

(a)
3 marks
Write similarity measures for clustering graph and network data.
(b)
4 marks
Explain Web Structure mining.
(c)
7 marksAsked in 3 of 7 papers
Write Applications of Distributed and parallel Data Mining.

Also asked in Summer 2026 Q5b OR, Summer 2024 Q5a OR

More Data Mining papers

Questions repeat across sessions. Working through two or three papers shows you which topics GTU asks most.

Summer 202670 marks · 5 questions
Winter 202570 marks · 5 questions
Summer 202570 marks · 5 questions
Summer 202470 marks · 5 questions

Other Semester 6 subjects

BE Computer

116AG01
Deep Learning and Neural Network
2160701
Software Engineering
2160704
Theory of Computation
2160707
Advanced Java

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About this paper

Official Gujarat Technological University (GTU) examination paper for Data Mining (Winter 2024, B.E. · Computer Engineering, Sem 6). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.

Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.

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