Machine Learning is a process which begins with observations of data to make better decisions of new data in future. Machine Learning algorithms divides as Supervised Machine Learning, Unsupervised Machine Learning, Semi- Supervised Machine Learning and Reinforcement Learning. In this paper, we focus on Supervised Machine Learning Algorithms especially its error rates. A Supervised learning algorithm analyses the training data and produces a classifier (conditional function), which can then be used for mapping test sets. We compare the various Supervised Machine Learning algorithms in terms of its error rates in this paper.

Supervised Machine Learning, Classifier, Error Rate

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