Fundamentals of Machine Learning 2022 Question Paper — Government Col…
The 2022 Fundamentals of Machine Learning previous year question paper (Government College of Engineering and Technology, Jammu), with every question and its marks.
- University: Government College of Engineering and Technology, Jammu
- Subject: Fundamentals of Machine Learning
- Course: Fundamentals of Machine Learning
- Branch: COMPUTER ENGINEERING
- Year: 2022
- Paper: end-term
- Duration: 180 minutes
- Total marks: 100
Instructions
- Attempt five questions in all selecting at least two questions from each Section.
- Each question carries 20 marks.
Questions
SECTION A
- QQ1 a). Explain the different data types in Python with examples. How do mutable and immutable types differ? [10 marks]
- Qb). Compare and contrast the usage of for loops and while loops with appropriate examples. [10 marks]
- QQ2 a). Compare and contrast machine learning with statistical modeling. Provide examples where each would be appropriate. [10 marks]
- Qb). Explain the concepts of overfitting and underfitting in machine learning models. How can they be addressed? [10 marks]
- QQ3 a). Explain the concept of simple linear regression. How is it different from multiple linear regression? [10 marks]
- Qb). Given the set of values: $X = (3, 9, 11, 5, 2)$ and $Y = (1, 8, 11, 4, 3)$. Evaluate the regression coefficients and also write the estimated regression equation. [10 marks]
- QQ4 a). Explain the role of functions in Python. How do you define a function and what are the different types of function arguments? [10 marks]
- Qb). Write a Python program to calculate the factorial of a number using recursion. Explain the recursion process. [10 marks]
SECTION B
- QQ5 a). Calculate precision, recall, F-score and accuracy for the following cases: True positive = 30, True Negative = 20, False positive = 10, False negative = 15 [10 marks]
- Qb). Given the following dataset of points, use the KNN algorithm to predict the class of a new point $(x,y) = (2.5, 3.0)$. Assume $k=3$. | $(x,y)$ | $(1,1)$ | $(2,2)$ | $(3,3)$ | $(6,5)$ | $(7,8)$ | $(8,8)$ | $(4,5)$ | $(5,7)$ | | :--- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | | Class | A | A | B | B | B | B | A | A | [10 marks]
- QQ6 a). Describe the basic concept of a decision tree in machine learning. How does the algorithm determine the splitting criteria at each node during recursive induction? [10 marks]
- Qb). Discuss the issues in decision tree learning and identify how to overcome it. [10 marks]
- QQ7 a). Illustrate the algorithm for K-means clustering of unsupervised learning. Write the disadvantages and applications of K-means clustering. [10 marks]
- Qb). Compare and contrast K-Means clustering with DBSCAN. What are the strengths and weaknesses of each? [10 marks]
- QQ8 a). Explain how collaborative filtering works and its advantages over content-based filtering. [10 marks]
- Qb). What is the primary purpose of logistic regression? How does the logistic (sigmoid) function transform the linear combination of features in logistic regression? [10 marks]