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EndsemNov 20232019 patternTE AI&DS

Machine Learning (ML) SPPU Endsem Question Paper Nov 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
Nov 2023
Max. marks
70
Time
2½ Hours
Semester
VII
Paper code
[6181]-102

Printed for: B.E. (Computer Engineering)

Instructions to the candidates

  1. Answer Q1 or Q2, Q3 or Q4, Q5 or Q6, Q7 or Q8.
  2. Neat diagrams must be drawn wherever necessary.
  3. Figures to the right side indicate full marks.
  4. Assume suitable data if necessary.

Questions

  1. Q1

    1. a)

      Differentiate between overfitting and underfitting.

      [6]
    2. b)

      The table below shows the number of grams of carbohydrates, X and the number of Calories, Y of six different foods. Find linear regression equation for this dataset. Carbohydrates (X) 8 9.5 10 6 7 4 Calories (Y) 12 138 147 88 108 62 Also find the value of Y for X = 12

      [8]
    3. c)

      Explain Bias Variance Trade off.

      [4]

  2. Q2

    1. a)

      What is Linear Regression? Explain the concept of Ridge regression.

      [9]
    2. b)

      Explain the following Evaluation Metrics : i) MAE ii) RMSE iii) R2

      [9]

  3. Q3

    1. a)

      Differentiate between bagging and boosting.

      [4]
    2. b)

      What is ensemble learning? Explain the concept of Random Forest ensemble learning.

      [9]
    3. c)

      What is the relation between precision and recall? Explain with an example.

      [4]

  4. Q4

    1. a)

      What is K-fold cross-validation? In K-fold cross-validation, comment on the following situations i) When the value of K is too large ii) When the value of K is too small. How do you decide the value of k in k-fold cross-validation?

      [9]
    2. b)

      Explain i) Accuracy, ii) Precision, iii) Recall, and iv) F-Score

      [8]

  5. Q5

    1. a)

      Explain K-Means clustering in detail with a suitable example.

      [8]
    2. b)

      What is outlier analysis? How is Local Outlier Factor detected?

      [5]
    3. c)

      Explain Spectral Cluster in galgorithm.

      [5]

  6. Q6

    1. a)

      Explain Hierarchical and Density-based Clustering approaches.

      [9]
    2. b)

      Write short note on : i) Optimization of clusters ii) K-Medoids iii) Evaluation metrics

      [9]

  7. Q7

    1. a)

      Write a note on Single Layer Neural Network.

      [4]
    2. b)

      Explain Radial Basis Function networks in detail.

      [8]
    3. c)

      Explain Recurrent Neural Networks and its applications in brief.

      Also asked:Nov 2025

      [5]

  8. Q8

    1. a)

      Explain the concept of Back Propagation in ANN with example.

      [8]
    2. b)

      What is Functional Link Artificial Neural Network (FLANN)? Explain its merits over other ANNs.

      [5]
    3. c)

      What is Activation Function? Explain with a suitable example. 

      [4]