An Empirical Comparison of ID3 and Back-propagation

AI and connectionist approaches to learning from examples differ in knowledge-base representation and inductive mechanisms. To explore these differences we experiment with a system from each paradigm: 1D3 and back-propagation. We compare the systems on the basis of both prediction accuracy and length of training. The systems show distinct performance differences across a variety of domains. We identify aspects of each system that may account for these performance differences. Finally, we suggest paths for cross-paradigm interaction.

• Type: Conference
• Year: 1989
• Where: IJCAI
• Authors: Douglas H. Fisher, Kathleen B. McKusick
• Keywords: Connectionist Approaches, Distinct Performance Differences, IJCAI 1989, IJCAI 2007, Performance Differences