r/MachineLearning - [D] Machine Learning - WAYR (What Are You Reading) - Week 63

My thesis is on a proposed algorithm similar to random forest but my degree is applied statistic. It also highlight the differences in model evaluation, statisticians go through 2-3 phases of model selection and a person who does ML go through 2 phases. The model evaluation phase is combined into one phase in ML and aren't needed when prediction is the most important thing. It highly the fact the high dimensional data such as genetic assays are being misinterpreted in the biology world. If you have more degree of freedom than the number of observations you can't be choosing one marker out of millions.