000 02027nam a2200277 a 4500
001 vtls000054748
003 KUKTEM
005 20251117150442.0
008 110714t2010 paua f b 001 0 eng d
020 _a9781605668109 (hbk.)
020 _a9781605668116 (ebook)
039 9 _a201112161235
_bfauzi
_y201107141220
_zsri
040 _aUMP
090 _aQ325.5 .N35 2010
100 1 _aNaidenova, Xenia
245 1 0 _aMachine learning methods for commonsense reasoning processes :
_binteractive models /
_cXenia Naidenova
260 _aHershey, PA :
_bInformation Science Reference,
_cc2010
300 _axiv, 410 p. :
_bill. ;
_c29 cm.
504 _aIncludes bibliographical references (p. 400-401) and index
505 0 _aKnowledge in the psychology of thinking and mathematics -- Logic-based reasoning in the framework of artiticial intelligence -- The coordination of commonsense reasoning operations -- The logical rules of commonsense reasoning -- The examples of human connonsense reasoning processes -- Machine learning (ML) as a diagnostic task -- The concept of good classification (diagnostic) test -- The duality of good diagnostic tests -- Towards an integrative model of deductive-inductive commonsense reasoning -- Towards a model of fuzzy commonsense reasoning -- Object-oriented technology for expert system generation -- Case technology for psycho-diagnostic system generation -- Commonsense reasoning in intelligent computer systems
520 _a"The main purpose of this book is to demonstrate the possibility of transforming a large class of machine learning algorithms into integrated commonsense reasoning processes in which inductive and deductive inferences are not separated one from another but moreover they are correlated and support one another"--Provided by publisher
650 0 _aMachine learning
650 0 _aCorrelation (Statistics)
650 0 _aRecursive partitioning
999 _aVIRTUA40
_c58651
_d58657
999 _aVTLSSORT0080*0200*0201*0400*0900*1000*2450*2600*3000*5040*5050*5200*6500*6501*6502*9991