Abstract: Supervised machine learning approaches have been widely used in many applications. In this paper approaches namely Na´ve Bayes, Bayesian Net, J48, Random Forest and KNN have been discussed. These algorithms are tested for sample dataset which is present in raw form. Then normalization is performed on this dataset. Precision and Accuracy has been compared for all these algorithms before and after normalization. Implementation of all these algorithms has been done using Weka. Weka is an open source tool for machine learning.
Keywords: Supervised machine learning, normalization, Weka.