ML Classification vs traditional programming
Hi, I was working on a classification exercise here - <a href=" removed link "> removed link and realized that I need to determine a threshold to classify if a place is livable (1) or not livable(0).
I have developed several such programs using traditional programming approaches (JAVA/.NET) so what would be advantages of ML here? Bear with me if it is a stupid question.
It's not a stupid question!
As a programmer, I recommend you to train a Machine Learning classifier and run your algorithm to your task, and then you can compare the results with traditional programming.
I always prefer to try things by myself, so just try it!
And to simplify some concepts, traditional programming is a manual process that a programmer creates the program without anyone programming the logic, one has to manually formulate or code rules, while machine learning is an automated process, so it can increase the value of your embedded analytics in many areas, including natural language interfaces, automatic outlier detection, recommendations, and causality and significance detection. All of these features help speed user insights and reduce decision bias.