Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/19312
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dc.contributor.advisorKumar, U Dinesh
dc.contributor.authorNallamothu, Nikita
dc.contributor.authorKumar, Nikhil
dc.date.accessioned2021-06-07T12:22:03Z-
dc.date.available2021-06-07T12:22:03Z-
dc.date.issued2018
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/19312-
dc.description.abstractThe objective of this CCS is to come up with a predictive model to predict which of the passengers survived Titanic ship wreck. In particular, the response variable “Survived” will be modelled given ten possible predictors. The remainder of this report includes background on the methods used to build the predictive model, specifically linear and logistic regression, Ada boost and random forests.
dc.publisherIndian Institute of Management Bangalore
dc.relation.ispartofseriesPGP_CCS_P18_089
dc.subjectMachine learning
dc.titleTitanic: Machine learning from disaster
dc.typeCCS Project Report-PGP
dc.pages21p.
Appears in Collections:2018
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