Evaluating a Machine Learning Algorithm

A TOOL BOX for ‘WHAT TO TRY NEXT?’

With abundance of easy-to-use Machine Learning Libraries, it is often appealing to apply them and achieve greater than 80% prediction accuracy in most cases. But, 'WHAT TO TRY NEXT?' is a question that buzz me and may be other aspiring Data Scientists too.

During my course ‘Machine Learning — Stanford Online’ at Coursera, Prof. Andrew Ng helped me sail through it. I hope this article, which briefs his explanation during one of his lectures, will help many of us to understand the importance of ‘debugging or diagnosing a learning algorithm’.