Anastasios Kyrillidis, Amir Kalev, et al.
npj Quantum Information
We study the effectiveness of non-uniform randomized feature selection in decision tree classification. We experimentally evaluate two feature selection methodologies, based on information extracted from the provided dataset: (i) leverage scores-based and (ii) norm-based feature selection. Experimental evaluation of the proposed feature selection techniques indicate that such approaches might be more effective compared to naive uniform feature selection and moreover having comparable performance to the random forest algorithm [3]. © 2014 IEEE.
Anastasios Kyrillidis, Amir Kalev, et al.
npj Quantum Information
Po-Sen Huang, Haim Avron, et al.
ICASSP 2014
Dmitry Malioutov, Aleksandr Aravkin
ICASSP 2014
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ICASSP 2014