I am asked to develop a classifier which can map vectors according to its class. I was told we basically must implement this formula. I will be using python. I have watch many videos on bayes classifiers but I am still struggling with this formula. Can someone please explain this to me and the prior steps to implement it, knowing that I have a training data set and test data set? This formula was titled "log likelihood". I believe it is for calculating the error rate of the classifier one implemented, so please let me know how I should actually implement the classifier from the bayes theorem.
Pomdapi113 t1_iy612tc wrote
Reply to [D] Simple Questions Thread by AutoModerator
I am asked to develop a classifier which can map vectors according to its class. I was told we basically must implement this formula. I will be using python. I have watch many videos on bayes classifiers but I am still struggling with this formula. Can someone please explain this to me and the prior steps to implement it, knowing that I have a training data set and test data set? This formula was titled "log likelihood". I believe it is for calculating the error rate of the classifier one implemented, so please let me know how I should actually implement the classifier from the bayes theorem.
picture of the formula