Artificial Intelligence & Machine Learning (AIML) SPPU Endsem Question Paper May 2024

Questions

1. Q1

   1. a)

      State and explain need of Regression analysis.

      [4]
   2. b)

      How gradient descent does helps to optimize linear regression model?

      [6]
   3. c)

      What are the different ways to prevent overfitting and underfitting.

      [8]
   OR

2. Q2

   1. a)

      What are different cost functions to access the performance of linear Regression model? In the given Dataset the outliers represent anomalies. Which cost function will be more suitable and why?

      [5]
   2. b)

      Define of Multivariate Regression and State advantages and disadvantages of Multivariate Regression.

      [5]
   3. c)

      Consider the following data : Prize in Rs Amount Demanded 1 10 40 2 11 38 3 16 48 4 18 40 5 20 60 i) Find values of  0 and  1 w.r.t. linear regression model which best fits given data. ii) Interpret and explain equation of regression line. iii) Estimate the likely demand when the price is Rs.15.

      [8]

3. Q3

   1. a)

      Consider following data. Which feature will be selected as a root node? Use Information Gain. Played football is dependent feature. Outlook Temperature Humidity Wind Played football (Yes/No) Sunny Hot High Weak No Sunny Hot High Strong No Overcast Hot High Weak Yes Rain Mild High Weak Yes Rain Cool Normal Weak Yes Rain Cool Normal Strong No Overcast Cool Normal Strong Yes Sunny Mild High Weak No Sunny Cool Normal Weak Yes Rain Mild Normal Weak Yes Sunny Mild Normal Strong Yes Overcast Mild High Strong Yes Overcast Hot Normal Weak Yes Rain Mild High Strong No

      [10]
   2. b)

      Define and Explain following terms i) Bayesian Network ii) Advantages and disadvantages of Naïve Bayes Classifier

      Also asked:Nov 2022

      [7]
   OR

4. Q4

   1. a)

      For the given data set apply Naive Bayes Classifier and predict the Class for Type of Type of family structure=Single Parent, Age group=Young, and Income status=Low Type of family Age group Income status Will they buy a car structure Nuclear Young Low Yes Extended Old Low No Childless Middle-aged Low No Childless Young Medium Yes Single Parent Middle-aged Medium Yes Childless Young Low No Nuclear Old High Yes Nuclear Middle-aged Medium Yes Extended Middle-aged High Yes Single Parent Old Low No

      [10]
   2. b)

      Define and explain following terms i) Minority Class ii) Gini Index iii) Entropy iv) Information Gain

      [7]

5. Q5

   1. a)

      Find all association rules in the following database in the following database with minimum support =2 and minimum confidence = 75%. Transactions Data Items 1 Bread, Milk, Diaper 2 Bread, Milk, Diaper, Coke 3 Diaper, Beer, Eggs 4 Bread, Milk, Coke

      [10]
   2. b)

      State & explain with appropriate example different types of linkage use in clustering.

      [8]
   OR

6. Q6

   1. a)

      Explain following Terms i) Rule ii) Support iii) Lift iv) Confidence

      Also asked:Nov 2022

      [8]
   2. b)

      Apply KNN on the Following data. Find class of person whose height is 170 cm and weight is 57 kg. Consider value K =5 and use Euclidian distance formula. Height (CM) Weight (KG) Class 167 51 Underweight 182 62 Normal 176 69 Normal 173 64 Normal 172 65 Normal 174 56 Underweight 169 58 Normal 173 57 Normal 170 55 Normal

      [10]

7. Q7

   1. a)

      With the help of suitable diagram explain Biological Neuron.

      [5]
   2. b)

      Explain the architecture of feed forward neural network. State its limitations.

      [7]
   3. c)

      What is deep learning? Explain different applications of deep learning.

      Also asked:Nov 2022

      [5]
   OR

8. Q8

   1. a)

      What is perceptron? Explain multilayer perceptron in detail.

      [5]
   2. b)

      Explain why we use non-linearity function? State and explain three types of neurons that add non-linearity in their computations.

      [7]
   3. c)

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

      [5]