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Machine Learning Proceedings 1993

Proceedings of the Tenth International Conference on Machine Learning, University of Massachusetts, Amherst, June 27-29, 1993

  • 1st Edition - July 1, 1993
  • Editor: Lawrence A. Birnbaum
  • Language: English
  • eBook ISBN:
    9 7 8 - 1 - 4 8 3 2 - 9 8 6 2 - 7

Machine Learning: Proceedings of the Tenth International Conference covers the papers presented at the Tenth International Conference on Machine Learning, held at Amherst,… Read more

Machine Learning Proceedings 1993

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Machine Learning: Proceedings of the Tenth International Conference covers the papers presented at the Tenth International Conference on Machine Learning, held at Amherst, Massachusetts in June 27-29, 1993. The book focuses on the advancements of techniques, practices, approaches, and methodologies in machine learning. The selection first offers information on automatic algorithm/model class selection, using decision trees to improve case-based learning, GALOIS, and multitask learning. Discussions focus on multitask connectionist learning in more detail; multitask decision trees; an algorithm for the incremental determination of the concept lattice; and empirical evaluation of GALOIS as a learning system. The text then examines the use of qualitative models to guide inductive learning; automation of path analysis for building causal models from data; and construction of hidden variables in Bayesian networks via conceptual clustering. The book ponders on synthesis of abstraction hierarchies for constraint satisfaction by clustering approximately equivalent objects; efficient domain-independent experimentation; learning search control knowledge for deep space network scheduling; and learning procedures from interactive natural language instructions. The selection is a dependable reference for researchers wanting to explore the field of machine learning.