CS-503 (B) RGPV B.Tech
Pattern Recognition (PR)
Previous year papers and the official syllabus are free to read, no account needed.
Previous Year Papers
1 paper, latest Nov 2023
Syllabus, notes and important questions for CS-503 (B)
Syllabus units
Topics as the official RGPV syllabus lists them.
Unit 1 Introduction 12 topics
- Definitions
- Data sets for Pattern
- Application Areas and Examples of pattern recognition
- Design principles of pattern recognition system
- Classification and clustering
- Supervised Learning
- Unsupervised learning and adaptation
- Pattern recognition approaches
- Decision Boundaries
- Decision region
- Metric spaces
- Distances
Unit 2 Classification 15 topics
- Introduction
- Application of classification
- Types of classification
- Decision tree
- Naïve Bayes
- Logistic regression
- Support vector machine
- Random forest
- K Nearest Neighbour Classifier and variants
- Efficient algorithms for nearest neighbour classification
- Different Approaches to Prototype Selection
- Combination of Classifiers
- Training set
- Test set
- Standardization and normalization
Unit 3 Unsupervised Learning & Clustering 7 topics
- Different Paradigms of Pattern Recognition
- Representations of Patterns and Classes
- Unsupervised Learning & Clustering
- Criterion functions for clustering
- Clustering Techniques: Iterative square‑error partitional clustering – K means
- Hierarchical clustering
- Cluster validation
Unit 4 Feature Extraction and Selection 6 topics
- Introduction of feature extraction and feature selection
- Types of feature extraction
- Problem statement and Uses
- Branch and bound algorithm
- Sequential forward / backward selection algorithms
- (l,r) algorithm
Unit 5 Recent Advances 10 topics
- Recent advances in Pattern Recognition
- Structural PR
- SVMs
- FCM
- Soft computing and Neuro‑fuzzy techniques
- Real‑life examples
- Histogram rules
- Density estimation
- Nearest Neighbor Rule
- Fuzzy classification