000 04057nam a22005895i 4500
999 _c11898
_d11898
001 978-3-319-55312-2
003 DE-He213
005 20211125101719.0
008 170330s2017 gw | s |||| 0|eng d
020 _a9783319553122
040 _cAIKTC-KRRC
041 _aENG
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aKulkarni, Parag.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aReverse Hypothesis Machine Learning
_h[electronic resource] :
_bA Practitioner's Perspective /
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXVI, 138 p. 61 illus., 9 illus. in color.
_bCard Paper
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v128
520 _aThis book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same—the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as well as machine intelligence enthusiasts. It can also used by practitioners to develop new machine learning applications to solve problems that require creativity.
650 0 _aComputer Engineering
_94622
653 _aComputational Intelligence.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319553115
776 0 8 _iPrinted edition:
_z9783319553139
776 0 8 _iPrinted edition:
_z9783319856261
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v128
856 4 0 _uhttps://doi.org/10.1007/978-3-319-55312-2
_zClick here to access eBook in Springer Nature platform. (Within Campus only.)
942 _cEBOOKS
_2ddc