Sensible Machine Learning
November 2, 2018
There are many choices and assumptions to make when designing a machine learning (ML) based system. Taking the common choice is appealing but can undermine your system performance. Having recently designed an ML based system for prediction of gene expression (GE) [1], we made various uncommon but sensible choices and assumptions given the particular problem […]