GTU · BE Computer · Semester 6
GTU 3160714 Data Mining Old Question Papers PDF
Official Gujarat Technological University (GTU) old question papers PDF (Regular & Remedial) and step-by-step solved questions for Data Mining across 2023 – 2026 examinations.
27 questions GTU asked more than onceAsked in all 7 papers: Describe the steps involved in data mining when viewed as a process of knowledge discovery.See listExam papers
Most repeated questions
27 questions GTU set in two or more of 7 papers, most repeated first. Tap a year to open that paper at the question.
Describe the steps involved in data mining when viewed as a process of knowledge discovery.
Summer 2026 Q1c Winter 2025 Q2c Summer 2025 Q1b Winter 2024 Q1c Summer 2024 Q1b Winter 2023 Q1c Summer 2023 Q1c
Explain decision tree algorithm with suitable example.
Winter 2025 Q3c Summer 2025 Q4c Winter 2024 Q3c Summer 2024 Q4c Winter 2023 Q3c
Explain the major issues in data mining
Summer 2026 Q2c Winter 2025 Q1b Summer 2024 Q1c Winter 2023 Q5c
Write and discuss the algorithm which is used to generate frequent itemsets using an iterative level-wise approach based on candidate generation.
Summer 2026 Q4c Winter 2025 Q1c Summer 2025 Q3c Summer 2024 Q3c OR
Describe various methods for handling the missing values in the dataset.
Summer 2025 Q2b Winter 2024 Q2a Summer 2024 Q2c Summer 2023 Q1b
How K-Mean clustering method differs from K-Medoid clustering method?
Summer 2026 Q5b Summer 2024 Q5b OR Winter 2023 Q5a Summer 2023 Q4b OR
Briefly explain outlier analysis.
Winter 2025 Q5a Summer 2025 Q5b Winter 2024 Q4b OR Summer 2023 Q3a OR
What are the requirements of clustering?
Summer 2025 Q5a Summer 2024 Q5c OR Winter 2023 Q4c OR Summer 2023 Q5b OR
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.
Differentiate clustering and classification.
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Dicuss the Applications of Distributed and parallel Data Mining.
What is the difference between “supervised” and unsupervised” learning?
Explain classification Vs. Prediction.
Explain Backpropagation algorithm.
What is web log? Explain web structure mining and web usage mining in detail.
Explain PAM algorithm.
Differentiate OLAP and OLTP.
How to handle noisy data?
Explain measures for finding rule interestingness (support,confidence) with example.
What are the attribute selection measures? Explain any one in details.
Explain Linear regression.
Draw the topology of a multilayer, feed-forward Neural Network.
Write a short note on: Web content mining.
Differentiate between partitioning and hierarchical methods for clustering.
What is Concept Hierarchy? List and explain types of Concept Hierarchy.
Briefly explain Linear and Non-linear regression.
Explain k-fold cross validation.
Which branches take this subject
GTU's syllabus lists 3160714 for 2 branches. One set of papers serves all of them.
Semester 6, elective: 2 branches
Computer Engineering, Computer Science & Engineering
Other Semester 6 subjects
Common questions
Are these GTU 3160714 Data Mining papers valid for both Regular and Remedial exams?
Yes. Gujarat Technological University (GTU) follows the same 70-mark syllabus, exam blueprint, and 23-mark passing cutoff for both Regular and Remedial (ATKT/backlog) examinations. All 7 past exam sessions (2023 – 2026) serve as comprehensive preparation for either attempt.
How can I download GTU 3160714 Data Mining old question papers PDF?
You can download official GTU 3160714 original question paper PDFs directly from the table above with 1 click and zero deceptive ads or wait timers. Every paper also includes interactive online questions with AI study prompts.
What is the passing mark for GTU Data Mining (3160714)?
The external theory exam carries 70 marks. The minimum passing cutoff is 23 marks (33%). Exam duration is 2.5 hours.
What is the GTU exam pattern for 3160714?
The examination contains 5 main questions of 14 marks each, totaling 70 marks. Questions 2 through 5 provide internal OR choices, typically split into 3-mark, 4-mark, and 7-mark questions.