Pattern Recognition (CS-503 (B)) - Important Questions

Differentiate between supervised learning and unsupervised learning with suitable examples.

Explain the various design principles of pattern recognition systems.

Define the following:

Explain how K-Nearest Neighbor works, including the KNN estimation algorithm and KNN decision rules.

Write a short note on any two:

Write a detail note on Random Forest.

What do you understand by normalization? Explain with example.

Explain an unsupervised learning / clustering algorithm with an example

What is pattern classification and what are the major paradigms of machine learning / pattern recognition?

Describe about cluster validation.

Discuss the various types of feature extraction methods.

Illustrate branch and bound Algorithm with suitable example.

Write an algorithm for forward selection with suitable example.

Describe about the of Neuro-Fuzzy and its Techniques.

State and explain the rules of Histogram in detail.