Phylosoc 2012: Apply Machine Learning Algorithm(s) to Ecology Data

by Abu Zaher Md. Faridee for National Evolutionary Synthesis Center

With the prevalence of 16S sequence data there is a need for ecologists to classify different populations associated with different conditions. To this end, the goal of this project is to create a program that will allow microbial ecologists to apply machine learning algorithms (e.g. random forests, classifiers) to microbial ecology data so they can identify bacterial populations that are associated with differences between health and disease.