Data pruning based outlier detection

dc.contributor.guide	Nandi, Sukumar and Deka, Jatindra Kr
dc.coverage.spatial	Computer Science and Engineering
dc.creator.researcher	Pamula, Rajendra
dc.date.accessioned	2023-05-09T06:17:10Z
dc.date.available	2023-05-09T06:17:10Z
dc.date.awarded	2015
dc.date.completed	2015
dc.date.registered	2005
dc.description.abstract	Due to the advancement of the data storage and processing capabilities of computers most of the real life applications are shifted to digital domains and many of them are data intensive In general most of the applications deal with similar type of data items but due to variety of reasons some data points are present in the data set which are deviating from the normal behaviors of common data points Such type of data points are referred as outliers and in general the number of outliers in a
dc.description.note	Not Available
dc.format.accompanyingmaterial	None
dc.format.dimensions	Not Available
dc.format.extent	Not Available
dc.identifier.uri	http://hdl.handle.net/10603/481805
dc.language	English
dc.publisher.institution	Department of Computer Science and Engineering
dc.publisher.place	Guwahati
dc.publisher.university	Indian Institute of Technology Guwahati
dc.relation	Not Available
dc.rights	self
dc.source.university	University
dc.subject.keyword	Computer Science
dc.subject.keyword	Computer Science Artificial Intelligence
dc.subject.keyword	Engineering and Technology
dc.title	Data pruning based outlier detection
dc.title.alternative	Not available
dc.type.degree	Ph.D.