Evaluation of logistic regression and random forest classification based on prediction accuracy and metadata analysis

Model selection is an important part of classification. In this thesis we study the two classification models logistic regression and random forest. They are compared and evaluated based on prediction accuracy and metadata analysis. The models were trained on 25 diverse datasets. We calculated the p...

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Bibliographic Details
Main Author: Wålinder, Andreas
Format: Others
Language:English
Published: Linnéuniversitetet, Institutionen för matematik (MA) 2014
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-35126