Title :
Using background knowledge to improve inductive learning: a case study in molecular biology
Author :
Hirsh, Haym ; Noordewier, Michiel
Author_Institution :
Dept. of Comput. Sci., Rutgers Univ., Piscataway, NJ, USA
Abstract :
This work uses background knowledge to reexpress training data in a form more appropriate for inductive learning. The approach dramatically improves the results of decision-tree and neural network learning methods.<>
Keywords :
DNA; learning by example; molecular biophysics; neural nets; background knowledge; case study; decision-tree; inductive learning; learning; molecular biology; neural network; training data; Computer aided software engineering; DNA; Encoding; Laboratories; Microorganisms; Sampling methods; Sequences; Signal processing; Speech; Training data;
Journal_Title :
IEEE Expert
