Important RGPV Question
CS- 503 (B) Pattern Recognition
V Sem, CS
UNIT 1- Introduction
Q.1) Explain various Design principles of Pattern Recognition systems.
(RGPV Nov 2023)
Q.2) Differentiate between supervised learning and unsupervised learning with suitable example.
(RGPV Nov 2023)
Q.3) What is pattern recognition? Explain it.
(RGPV June 2020)
Q.4) Differentiate learning and adaptation.
(RGPV June 2020)
Q.5) Differentiate supervised learning and unsupervised learning.
(RGPV June 2020)
Q.6) Discuss any unsupervised learning algorithm with an example.
(RGPV June 2020)
UNIT 2- Classification
Q.1) Write a detail note on Random Forest.
(RGPV Nov 2023)
Q.2) How does K-Nearest Neighbor works? Explain with KNN estimation and KNN rules.
(RGPV Nov 2023)
Q.3) What do you understand by normalization? Explain with
example.
(RGPV Nov 2023)
Q.4) How do we evaluate the performance of a classifier?
(RGPV June 2020)
Q.5) Write an algorithm for k-Nearest neighbour estimation.
(RGPV June 2020)
Q.6) How the k-nearest neighbour method works? Explain with KNN estimation and KNN rule.
(RGPV June 2020)
Q.7) Write the difference between classification and clustering.
(RGPV June 2020)
Q.8) How do we evaluate the performance of a classifier?
(RGPV June 2020)
UNIT 3- Different Paradigms of Pattern Recognition
Q.1) Describe about cluster validation.
(RGPV Nov 2023)
Q.2) Enlist the clustering Techniques. Explain any one Technique.
(RGPV Nov 2023)
Q.3) State and explain the different paradigms of pattern recognition.
(RGPV Nov 2023)
Q.4) What is pattern classification? What are major paradigms of machine learning?
(RGPV June 2020)
Q.5) Explain chi-square test in detail.
(RGPV June 2020)
Q.6) What do you mean by hierarchical clustering explain?
(RGPV June 2020)
UNIT 4- Introduction of feature extraction and feature selection
Q.1) Discuss the various types of feature extraction.
(RGPV Nov 2023)
Q.2) Illustrate branch and bound Algorithm with suitable
example.
(RGPV Nov 2023)
Q.3) Write an algorithm for forward selection with suitable example.
(RGPV Nov 2023)
UNIT 5- Recent advances in Pattern Recognition
Q.1) Describe about the of Neuro-Fuzzy and its Techniques.
(RGPV Nov 2023)
Q.2) Why use Fuzzy classes? What is the Fuzzy classification process?
(RGPV Dec 2020)
Q.3)Explain the term parzen window, density estimation in brief.
(RGPV Dec 2020)
Q.4) What do you mean by fuzzy decision making?
(RGPV June 2020)
EXTRA QUESTIONS-
Q.1) Define the following
i) Clustering
11) Metric spaces
(RGPV Nov 2023)
Q.2) Write a short note on any two:
i) Data sets for pattern
ii) Training set
iii) Classifier and variants
iv) FCM
(RGPV Nov 2023)
Q.3) Write a short note on Gaussian mixture model.
(RGPV June, Dec 2020)
Q.4) What do you mean by discriminant function?
(RGPV Dec 2020)
Q.5) Explain the concept of Hidden Markov Model (HMM).
(RGPV Dec 2020)
Q.6) Discuss mean and covariance with an example.
(RGPV Dec 2020)
Q.7) What is dimension reduction? Explain.
(RGPV Dec 2020)
Q.8) Write short note on any three.
i) Clustering
ii) Chi-square test
iii) Forward algorithm
iv) Back ward algorithm
v) Maximum likelihood estimation
(RGPV Dec 2020)
Q.9) What is the probability of obtaining 9,10 and 11 points with 3 dice?
(RGPV June, Dec 2020)
Q.10) Define the law of total probability.
(RGPV June 2020)
Q.11) What are different components of a learning system.
(RGPV June 2020)
Q.12) Explain maximum likelihood estimation with suitable example.
(RGPV June 2020)
Q.13) Write short note on any three.
i) Perzen window
ii) Density estimation
iii) Learning
iv) Adaptation
v) Cluster validation
(RGPV June 2020)
— Best of Luck for Exam —
