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Abstract
Growth of internet and its commercialization from past decades make it important to separate and compete with other similar websites especially the E- commerce based websites which sell products directly to the customers. In order to classify the webpages based on feature extraction, five machine learning classifiers have been compared to evaluate theperformance in which decision tree gives more accuracy in true classification. The diverse Classifiers compared are: Support Vector Machines (SVM), K-nearest neighbor, Artificial neural network, Naïve-Bayes and Decision trees Average accuracy for true classification by all classifiers is in between 75% to 99.5% in which decision tree gives almost above 99% percent accuracy in true classification.