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InsemOct 20242019 patternTE IT

Artificial Intelligence & Machine Learning (AIML) SPPU Insem Question Paper Oct 2024

All 4 questions from this SPPU insem paper, as printed. Read them here or open the PDF.

Open the PDFMost repeated AIML questions
Subject code
314443
Pattern
2019 pattern
Exam
Insem
Session
Oct 2024
Max. marks
30
Time
1 Hour
Semester
I
Paper code
[6360]-57

Printed for: T.E. (IT) (Insem.)

Instructions to the candidates

  1. Answer Q1 or Q2, Q3 or Q4.
  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)

      Explain with example Predictive and Descriptive tasks of Machine Learning. Also state Predictive and Descriptive Model (CO1).

      [6]
    2. b)

      Explain k-fold Cros Validation technique with example (CO1).

      [5]
    3. c)

      Write a note on Principal Component Analysis (PCA) (CO1)

      [4]

  2. Q2

    1. a)

      Justify which type of learning could be the most appropriate, considering any one real world application of Machine Learning also explain your reasoning (CO1).

      [6]
    2. b)

      Explain Reinforcement Learning with diagram (CO1).

      [5]
    3. c)

      Discuss various scales of measurement of features in machine learning (CO1).

      [4]

  3. Q3

    1. a)

      What is multiclass classification? Explain One-Vs-Rest and One-vs- One multiclass classifier construction method with suitable example (CO2).

      Also asked:Oct 2022

      [6]
    2. b)

      Explain true positive, true negative, false positive, false negative and class ratio for classification task (CO2).

      [5]
    3. c)

      Explain linear Support vector machine with suitable diagram (CO2).

      Also asked:Oct 2022

      [4]

  4. Q4

    1. a)

      What is binary classification? Consider the following confusion matrix: Predicated + – Total + 25 5 30 Actual – 10 20 30 Total 35 25 60 Calculate i) Recall ii) Precision iii) Accuracy iv) F1-score v) Justify which evaluation measures will be more suitable for above matrix (CO2).

      [6]
    2. b)

      What are support vectors in Support vector Machine? Explain Hard and soft margin SVM with the suitable diagram (CO2).

      [5]
    3. c)

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

      [4]