The Dow Chemical Company

Erik David Goodman

Chun S Wang

John M Wassick

Kalyanmoy Deb

Yashesh Deepakkumer Dhebar

Vicki Rothhaar

John Martin Wassick

Chun Wang

An embodiment involves a hybrid machine learning classifier that uses a random forest of decision tree classifiers to predict a tariff code prefix, and uses a plurality of expert trees to predict a tariff code suffix from properties related to chemical components associated with the respective tariff code prefixes. The embodiment also involves: determining a proportion of a dominant chemical component in comparison to other chemical components in a new set of chemical components; calculating similarity scores for the new set of chemical components and words associated with the tariff code prefixes; generating a feature vector from the proportion and the similarity scores; and obtaining a predicted tariff code including a predicted tariff code prefix determined by applying the random forest to the feature vector, and a predicted tariff code suffix determined by traversing a particular expert tree in accordance with properties related to the new set of chemical components.

Hybrid machine learning model for code classification

Growing community of inventors

East Lansing, MI, United States of America

Erik David Goodman