The previous post: Find your best fit This post is a continuation of the previous one. This one shall discuss a few more ways of evaluating a Machine Learning Algorithm - a Classification Model, in particular. Learning Curve Say we have fit some function to 'x' number of training samples. The error of this function … Continue reading Evaluating your Classifier
Find your Best Fit!
Let's say we have chosen and implemented the best Machine Learning Algorithm, suitable for the data of our choice but ended up figuring out that the algorithm is actually making unacceptably large errors in prediction. What do we do next? Let's discuss some choices that can be made in such a scenario and also get … Continue reading Find your Best Fit!