Assessing Learning Paradigms in Text Classification Using ML - Wajeed, Mohammed Abdul
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Text categorization has become the core research area in text mining domain. Semi-supervised learning paradigm is relatively new learning paradigm compared to supervised and unsupervised learning, semi-supervised learning paradigm is introduced. The topics in the book are introduced such that a novice reader can grasp them easily. The simple to implement, traditional K-Nearest Neighbour learning algorithm is employed in the process of categorization. Terms importance with respect to each class label are identified and are used to improve the performance of the traditional KNN algorithm.

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Produktbeschreibung
Text categorization has become the core research area in text mining domain. Semi-supervised learning paradigm is relatively new learning paradigm compared to supervised and unsupervised learning, semi-supervised learning paradigm is introduced. The topics in the book are introduced such that a novice reader can grasp them easily. The simple to implement, traditional K-Nearest Neighbour learning algorithm is employed in the process of categorization. Terms importance with respect to each class label are identified and are used to improve the performance of the traditional KNN algorithm.
Autorenporträt
Dr. Mohammed Abdul Wajeed currently works for Keshav Memorial Institute of Technology, Hyderabad in Computer Science & Engineering Department. He completed M.Tech Computer Science & Engineering from Osmania University in 2007, and PHD in Computer Science & Engineering from Jawahar Lal Nehru Technological University in 2015.