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EndsemNov 20242019 patternBE AI&DS

Machine Learning (ML) SPPU Endsem Question Paper Nov 2024

All 8 questions from this SPPU endsem paper, as printed. Read them here or open the PDF.

Open the PDFMost repeated ML questions
Subject code
417521
Pattern
2019 pattern
Exam
Endsem
Session
Nov 2024
Max. marks
70
Time
2½ Hours
Semester
VII
Paper code
[6354]-781

Printed for: B.E. (AIDS)

Instructions to the candidates

  1. Answer Q1 or Q2, Q3 or Q4, Q5 or Q6, Q7 or Q8.
  2. Neat diagrams mus be drawn wherever necessary
  3. Figures to the right indicates full Marks
  4. Use of electronic pocket calculator is allowed

Questions

  1. Q1

    1. a)

      What are kernel functions in SVM? Describe the Radial Basis Kernel, and Sigmoid kernel.

      Also asked:Nov 2025

      [6]
    2. b)

      Write formula for accuracy, precision, recall and fl-score. Calculate accuracy, precision, recall and fl-score for given example. Actual Values Cancer No Cancer 45 18 12 25

      [12]

  2. Q2

    1. a)

      Explain any 4 evaluation measures of Multiclass classification.

      Also asked:Nov 2023

      [4]
    2. b)

      Differentiate Balanced and Imbalanced Classification.

      Also asked:Nov 2025

      [6]
    3. c)

      Write a detailed note on K Nearest Neighbour algorithm with suitable example.

      [8]

  3. Q3

    1. a)

      Differentiate Agglomerative Hierarchical Clustering and Divisive Hierarchical Clustering.

      [8]
    2. b)

      What is clustering? Elaborate Types of Clustering.

      [9]

  4. Q4

    1. a)

      Explain DBSCAN algorithm with advantages and disadvantages.

      Also asked:Nov 2025

      [8]
    2. b)

      Describe centroid based clustering algorithm and explain any one type with example. Predicted Values No Cancer Cancer 2

      [9]

  5. Q5

    1. a)

      Explain Following with respect to Ensemble learning. i) Need of Ensemble Learning ii) Advantages of Ensemble methods iii) Ensemble learning limitations

      [9]
    2. b)

      Elaborate stacking approach of ensemble with example.

      [9]

  6. Q6

    1. a)

      Describe ensemble learning. Explain Gradient Boosting ensemble learning techniques.

      [9]
    2. b)

      Explain any three voting mechanism in ensemble learning.

      [9]

  7. Q7

    1. a)

      Differentiate supervised and unsupervised learning with example.

      Also asked:Aug 2025 ·Sep 2023

      [8]
    2. b)

      Explain Reinforcement Learning need and its types in detail?

      [9]

  8. Q8

    1. a)

      Explain following terms: i) Belman Equation ii) Markov Chain iii) Q table iv) Q function

      [8]
    2. b)

      How does the Markov property relate to Reinforcement Learning? Why is it important? 

      [9]