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  • 12:08 PM, Wednesday, 20 Nov 2019


Course Undergraduate
Semester Electives
Subject Code AV489
Subject Title Pattern Recognition and Machine Learning

Syllabus

PR overview-Feature extraction-Statistical Pattern Recognition-Supervised Learning-Parametric
methods-Non parametric methods; ML estimation-Bayes estimation-k NN
approaches. Dimensionality reduction, data normalization. Regression, and time series
analysis. Linear discriminat functions. Fishers linear discriminant, linear perceptron and Neural
Networks. Kernel methods and Support vector machine. Unsupervised learning and clustering.
K-means and hierarchical clustering. Ensemble/ Adaboost classifier, Soft computing paradigms
for classification and clustering. Applications to document analysis and recognition

Text Books
References