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020 _a9783540687085
_9978-3-540-68708-5
024 7 _a10.1007/3-540-62858-4
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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082 0 4 _a006.3
_223
245 1 0 _aMachine Learning: ECML'97
_h[electronic resource] :
_b9th European Conference on Machine Learning, Prague, Czech Republic, April 23 - 25, 1997, Proceedings /
_cedited by Maarten van Someren, Gerhard Widmer.
250 _a1st ed. 1997.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c1997.
300 _aXIV, 366 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v1224
505 0 _aUncertain learning agents -- Constructing and sharing perceptual distinctions -- On prediction by data compression -- Induction of feature terms with INDIE -- Exploiting qualitative knowledge to enhance skill acquisition -- Integrated learning and planning based on truncating temporal differences -- ?-subsumption for structural matching -- Classification by Voting Feature Intervals -- Constructing intermediate concepts by decomposition of real functions -- Conditions for Occam's razor applicability and noise elimination -- Learning different types of new attributes by combining the neural network and iterative attribute construction -- Metrics on terms and clauses -- Learning when negative examples abound -- A model for generalization based on confirmatory induction -- Learning Linear Constraints in Inductive Logic Programming -- Finite-Element methods with local triangulation refinement for continuous reinforcement learning problems -- Inductive Genetic Programming with Decision Trees -- Parallel anddistributed search for structure in multivariate time series -- Compression-based pruning of decision lists -- Probabilistic Incremental Program Evolution: Stochastic search through program space -- NeuroLinear: A system for extracting oblique decision rules from neural networks -- Inducing and using decision rules in the GRG knowledge discovery system -- Learning and exploitation do not conflict under minimax optimality -- Model combination in the multiple-data-batches scenario -- Search-based class discretization -- Natural ideal operators in Inductive Logic Programming -- A case study in loyalty and satisfaction research -- Ibots learn genuine team solutions -- Global data analysis and the fragmentation problem in decision tree induction -- Case-based learning: Beyond classification of feature vectors -- Empirical learning of Natural Language Processing tasks -- Human-Agent Interaction and Machine Learning -- Learning in dynamically changing domains: Theory revision and context dependence issues.
520 _aThis book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 revised full papers selected from a total of 73 submissions. Also included are an abstract and two papers corresponding to the invited talks as well as descriptions from four satellite workshops. The volume covers the whole spectrum of current machine learning issues.
650 0 _aArtificial intelligence.
650 0 _aAlgorithms.
650 1 4 _aArtificial Intelligence.
650 2 4 _aAlgorithms.
700 1 _aSomeren, Maarten van.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aWidmer, Gerhard.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540628583
776 0 8 _iPrinted edition:
_z9783662203620
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v1224
856 4 0 _uhttps://doi.org/10.1007/3-540-62858-4
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912 _aZDB-2-SXCS
912 _aZDB-2-LNC
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