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dc.contributor.authorHUSSAIN, MOHAMMAD FAIRZ-
dc.date.accessioned2022-02-21T08:40:44Z-
dc.date.available2022-02-21T08:40:44Z-
dc.date.issued2020-06-
dc.identifier.urihttp://dspace.dtu.ac.in:8080/jspui/handle/repository/18891-
dc.description.abstractHowever, training neural networks require large datasets, otherwise, it cannot give accurate classification. Inspite all the data availability, there are some issues which lack enough data. Medical images, rare animals species to name a few examples with relatively less number of information. In our experiment, we have taken the data from the heart deprtment, which tells the condition of the heart. We will be comparing the cross entropy loss function with out own loss function.en_US
dc.language.isoenen_US
dc.publisherDELHI TECHNOLOGICAL UNIVERSITYen_US
dc.relation.ispartofseriesTD - 5446;-
dc.subjectHEART DISEASEen_US
dc.subjectPATIENTSen_US
dc.subjectHEART DEPARTMENTen_US
dc.subjectCROSS ENTROPY LOSSen_US
dc.titlePREDICTING PRESENCE OF HEART DISEASE IN PATIENTS USING NEURAL NETWORKen_US
dc.typeThesisen_US
Appears in Collections:M.E./M.Tech. Information Technology

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