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EndsemMay 20232019 patternTE AI&DS

Machine Learning (ML) SPPU Endsem Question Paper May 2023

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
410242
Pattern
2019 pattern
Exam
Endsem
Session
May 2023
Max. marks
70
Time
2½ Hours
Semester
VII
Paper code
[6004]-481

Printed for: B.E. (Computer Engineering)

Instructions to the candidates

  1. Attempt Q.1 or Q.2, Q.3 or Q.4, Q.5 or Q.6 and Q.7 or Q.8.
  2. Figures to the right indicate full marks.
  3. Neat diagrams must be drawn wherever necessary.
  4. Assume suitable data, if necessary.

Questions

  1. Q1

    1. a)

      Explain the following terms with suitable examples. i) Bias ii) Variance iii) Under fitting and Over fitting

      [6]
    2. b)

      Differentiate between Lasso Regression and Ridge Regression.

      Also asked:May 2025

      [6]
    3. c)

      Explain gradient descent algorithm with example.

      [6]

  2. Q2

    1. a)

      What do you mean by regression? Explain with suitable example.

      [6]
    2. b)

      This part has equations that don’t show as text. Open the PDF to read it.

      [6]
    3. c)

      What is gradient descent? Compare batch gradient and stochastic gradient descent.

      [6]

  3. Q3

    1. a)

      Explain with example the variant of SVM, the support vector regression.

      [5]
    2. b)

      What do you mean by ensemble learning?Differentiate between bagging & boosting.

      Also asked:May 2025

      [6]
    3. c)

      What are different variants of multi-class classification? Explain them with suitable example. 2

      Also asked:Nov 2025

      [6]

  4. Q4

    1. a)

      This part has equations that don’t show as text. Open the PDF to read it.

      [6]
    2. b)

      Write a short note on : i) Random forest. ii) Adaboost.

      [6]
    3. c)

      Discuss K-nearest neighbour algorithm with suitable example.

      [5]

  5. Q5

    1. a)

      With reference to Clustering explain the issue of “Optimization of Clusters”.

      [6]
    2. b)

      Compare Hierarchical clustering and K-means clustering.

      [6]
    3. c)

      Explain how a cluster is formed in the density based clustering algorithm.

      [6]

  6. Q6

    1. a)

      How would you choose the number of clusters when designing a K- Medoid clustering algorithm?

      [6]
    2. b)

      Write a short note on out lier analysis with respect to clustering.

      [6]
    3. c)

      Differentiate between K-means and Spectral clustering.

      [6]

  7. Q7

    1. a)

      What are building blocks of neural network, elaborate?

      Also asked:Nov 2025 ·May 2024

      [5]
    2. b)

      Describe characteristics of back propagation algorithm.

      [6]
    3. c)

      Write a short note on Recurrent neural n/w & convolutional neural n/w.

      [6]

  8. Q8

    1. a)

      Explain artificial neural n/w based on perception concept with diagram.

      [6]
    2. b)

      Describe multi-layer neural n/w. Explain why back propagation algorithm is required.

      [6]
    3. c)

      Discuss any two activation functions with example. 

      [5]