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This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern representation and nearest neighbour based classifiers, current topics - neural networks, support vector machines and decision trees - attributed to the recent vast progress in this field are also dealt with. Introduction to Pattern Recognition and Machine Learning will equip readers, especially senior computer science undergraduates, with a deeper understanding of the subject matter.
Introduction; Representation; Nearest Neighbour Based Classifiers; Bayes Classifier; Decision Trees; Support Vector Machines; Combination of Classifiers; Clustering; Application: Handwritten Digit Recognition; Summary and Conclusions.
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- ID: 9789814335454
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