Machine Learning Techniques (BCS055) AKTU predicted paper 2026-27
AI-predicted paper for Machine Learning Techniques based on 9 past papers (2021, 2022, 2023, 2024, 2025, 2026). NOT an official AKTU paper. Use as a revision tool only.
Paper pattern
- Section A: Attempt all questions. (14 marks)
- Section B: Attempt any THREE questions out of five. (21 marks)
- Section C: Attempt ONE question from each pair (a or b). (35 marks)
Why these questions
- Unit 2 (Regression, Bayesian Learning and Support Vector Machine) dominates — 28% avg weightage
- Asked every year: Types of Learning, GA Cycle of Reproduction
- Due for comeback: Issues in Machine Learning, Concept Learning
- Low priority (never asked): Concept of 1D and 2D Convolution Layers, Training of Network
- Most repeated topic: Types of Learning
Section A – 2-mark questions
- Differentiate between supervised and unsupervised learning.
- Differentiate between linear and logistic regression.
- Explain the concept of overfitting in Decision Trees?
- What is backpropagation in neural networks?
- Write a short note on GA Cycle of Reproduction.
- Write a short note on Naive Bayes Classifier.
- Define k-Nearest Neighbor algorithm.
Section B – sample questions
- Describe the following concepts in decision tree in detail: (i) Avoiding overfitting in decision tree. (ii) Incorporating continuous valued attributes.
- Explain Genetic Algorithm cycle with suitable example.
- Explain k-Nearest Neighbour (k-NN) algorithm and its limitations.