PyQAlloy is a tool for detection of abnormal data in alloy datasets (and other chemical spaces), allowing removal of hard-to-find erros in the data which often introduce systematic errors throwing off machine learning and researchers alike. Its development is a part of ULTERA Project carried under the DOE ARPA-E ULTIMATE program that aims to develop a new generation of materials for turbine blades and related applications.
copied from cf-staging / pyqalloy