Prediction Models: Traditional versus Machine Learning - Jitendra Subramanyam

Machine learning models are constructed differently from traditional quantitative models. In the first type of traditional prediction model, the input data set along with statistical assumptions and calculations determine the prediction algorithm. The input data set is analyzed (or "fitted to the data") using statistical techniques. The prediction algorithm that is the one best suited to describing the data as determined by the statistical analysis. The second type of traditional prediction model uses an explicit set of rules (e.g., if X then Y) to transform the inputs into a prediction.