Assessing Learning Paradigms in Text Classification Using ML

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.