Pattern Recognition and Computer Vision - ASSIGNMENT 1

Date -- 30 September 2024

Explain the difference between supervised and unsupervised learning in pattern recognition.
What is the role of clustering in pattern recognition?
Discuss the advantages and limitations of using Decision Trees for pattern recognition.
Explain the concept of feature selection and its importance in pattern recognition.
Analyze the performance of different clustering algorithms (e.g., K-means, Hierarchical) on a gene expression dataset.
Prove that Naive Bayes classifiers are optimal when features are independent.
Explain the concept of maximum-margin hyperplane in SVMs.
Derive the SVM decision boundary equation.
Describe the role of bias terms in Feed Forward Networks.
Explain the difference between Fisher Discriminant Analysis and Principal Component Analysis.
What is the role of regularization in polynomial curve fitting?

Submit the assignment by mail at vaibhavnijhawan@mait.ac.in before 12 o' clock midnight, 14 October 2024.