Learning algorithm developed to mine large data sets
APR 03, 2014
DOI: 10.1063/PT.5.027815
Ars Technica : To analyze the explosion of data being generated in a range of scientific fields, an algorithm has been developed that works with minimal human supervision. Called KODAMA (knowledge discovery by accuracy maximization), it comprises five steps, one of which is iterative, to classify and evaluate the data and look for meaningful patterns. To test its accuracy, the developers have applied the algorithm to several data sets, including the linguistic characteristics of State of the Union addresses. In that exercise, KODAMA was able to identify a transition in vocabulary that occurred during Ronald Reagan’s presidency.
© 2014 American Institute of Physics
