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As the interest in machine learning and data mining springs up, the problem of how to assess learning algorithms and compare classifiers become more pressing. This has been associated with the lack of comprehensive and complete workflow depending on the project scale to provide guidance to its users. This means the success or failure of machine learning project can be highly dependent on the person or team carrying it and their existing knowledge on machine learning. Classifier Workflow provides eight-steps that machine learning experimenter have to follow while comparing machine learning classification techniques.