Probabilistic Inductive Logic Programming [electronic resource] : Theory and Applications / edited by Luc Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton.
Tipo de material:
TextoSeries Lecture Notes in Computer Science, 4911Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Descripción: VIII, 341 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783540786528Trabajos contenidos: SpringerLink (Online service)Tema(s): Computer science | Computer software | Data mining | Artificial intelligence | Bioinformatics | Computer Science | Artificial Intelligence (incl. Robotics) | Programming Techniques | Mathematical Logic and Formal Languages | Algorithm Analysis and Problem Complexity | Data Mining and Knowledge Discovery | Computational Biology/BioinformaticsFormatos físicos adicionales: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q334-342TJ210.2-211.495Recursos en línea: de clik aquí para ver el libro electrónico Probabilistic Inductive Logic Programming -- Formalisms and Systems -- Relational Sequence Learning -- Learning with Kernels and Logical Representations -- Markov Logic -- New Advances in Logic-Based Probabilistic Modeling by PRISM -- CLP( ): Constraint Logic Programming for Probabilistic Knowledge -- Basic Principles of Learning Bayesian Logic Programs -- The Independent Choice Logic and Beyond -- Applications -- Protein Fold Discovery Using Stochastic Logic Programs -- Probabilistic Logic Learning from Haplotype Data -- Model Revision from Temporal Logic Properties in Computational Systems Biology -- Theory -- A Behavioral Comparison of Some Probabilistic Logic Models -- Model-Theoretic Expressivity Analysis.
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