01796nam a2200229 a 4500001001400000003000700014005001700021008004100038020002500079020002600104040000800130100002100138245010600159260005700265300003400322504006300356505073200419520033801151650002101489650002901510650002701539vtls000054748KUKTEM20251117150442.0110714t2010    paua   f b    001 0 eng d  a9781605668109 (hbk.)  a9781605668116 (ebook)  aUMP1 aNaidenova, Xenia10aMachine learning methods for commonsense reasoning processes :binteractive models /cXenia Naidenova  aHershey, PA :bInformation Science Reference,cc2010  axiv, 410 p. :bill. ;c29 cm.  aIncludes bibliographical references (p. 400-401) and index0 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  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 0aMachine learning 0aCorrelation (Statistics) 0aRecursive partitioning