Learning by Switching Type of Information

The present work is dedicated to the study of modes of data-presentation in the range between text and informant within the framework of inductive inference. In this study, the learner alternatingly requests sequences of positive and negative data. We define various formalizations of valid data presentations in such a scenario. We resolve the relationships between these different formalizations, and show that one of these is equivalent to learning from informant. We also show a hierarchy formed (for each of the formalizations studied) by considering the number of switches between requests for positive and negative data.

• Type: Conference
• Year: 2001
• Where: ALT
• Authors: Sanjay Jain, Frank Stephan
• Keywords: ALT 2001, Inductive Inference, Machine Learning, Negative Data, Valid Data Presentations