Definite Detection of Categorization of Indian News by Using PART and FT Algorithm

Classification may refer to categorization, the process in which ideas and objects are recognized, differentiated, and understood. Classification is an important data mining technique with broad applications. It classifies data of various kinds. Recent developments of e-learning specifications such as Learning Object Metadata (LOM), Sharable Content Object Reference Model (SCORM), Learning Design and other pedagogy research in semantic e-learning have shown a trend of applying innovative computational techniques, especially Semantic Web technologies, to promote existing content-focused learning services to semantic-aware and personalised learning services. This paper has been carried out to make a performance evaluation of PART and FT classification algorithm. The paper sets out to make comparative evaluation of classifiers PART and FT in the context of dataset of Indian news to maximize true positive rate and minimize false positive rate. For processing Weka API were used. The results in the paper on dataset of Indian news also show that the efficiency and accuracy of FT is good than PART.