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EndsemNov 20222019 patternTE IT

Artificial Intelligence & Machine Learning (AIML) SPPU Endsem Question Paper Nov 2022

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

Open the PDFMost repeated AIML questions
Subject code
314443
Pattern
2019 pattern
Exam
Endsem
Session
Nov 2022
Max. marks
70
Time
2½ Hours
Semester
I
Paper code
[5926]-121

Printed for: T.E. (IT)

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 indicate full marks.
  4. Assume suitable data if necessary.

Questions

  1. Q1

    1. a)

      What do you mean by coefficient of regression? Explain SSE, MSE and MAE in context of regression. [CO2, L3]

      [5]
    2. b)

      What is multiple regression? How it is different from simple linear regression [CO2, L1]

      [5]
    3. c)

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

      [7]

  2. Q2

    1. a)

      Explain under fit, over fit and just fit models for Regression [CO2, L1]

      [5]
    2. b)

      Explain bias-variance dilemma [CO2, L2]

      [5]
    3. c)

      What is univariate and multivariate regression? Explain any three measures of Evaluation of performance of regression model. [CO2, L2]

      [7]

  3. Q3

    1. a)

      For the given data set apply Naïve Bayes Classifier and predict the Class for weather = Sunny and car = working. Weather Car Class Sunny Working Go-out Rainy Broken Go-out Sunny Working Go-out Sunny Working Go-out Sunny Working Go-out Rainy Broken Stay-home Rainy Broken Stay-home Sunny Working Stay-home Sunny Broken Stay-home Rainy Broken Stay-home [CO4, L3]

      [10]
    2. b)

      What is decision tree? Explain ID-3 algorithm of Decision tree in detail. [CO4, L2]

      [8]

  4. Q4

    1. a)

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

      [10]
    2. b)

      Define and Explain following terms i) Bayesian Network ii) Advantages and disadvantages of Naïve Bayes Classifier [CO4, L2] 3

      Also asked:May 2024

      [8]

  5. Q5

    1. a)

      Find all association rules using apriori algorithm in the following database in the following database with minimum support = 2 and minimum confidence = 65%. Transactions Data Items T1 Pen, Pencil, Notebook T2 Pencil, File T3 Pen, Pencil, Notebook, File T4 Pen, Notebook T5 Pencil, Scale, File T6 Pencil, Scale T7 Pen, Pencil, Scale [CO5, L3]

      [10]
    2. b)

      What is use of K-means algorithm? Explain Centroid and medoid? Explain different types of distances measures. [CO5, L2]

      [8]

  6. Q6

    1. a)

      Explain following Terms i) Rule ii) Support iii) Lift iv) Confidence [CO5, L2]

      Also asked:May 2024

      [8]
    2. b)

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

      [10]

  7. Q7

    1. a)

      With the help of suitable diagram explain Biological Neuron. [CO6, L3]

      [6]
    2. b)

      What is the use of activation function in Neural Network? Explain any two activation functions in detail [CO6, L2]

      [6]
    3. c)

      What is deep learning? Explain different applications of deep learning. [CO6, L1]

      Also asked:May 2024

      [5]

  8. Q8

    1. a)

      What is perceptron? Explain multilayer perceptron in detail. [CO6, L3]

      [6]
    2. b)

      Write a note on following activation functions. i) Sigmoid ii) Tanh iii) ReLU [CO6, L2]

      [6]
    3. c)

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

      [5]