Random Bits Forest: a Strong Classifier/Regressor for Big Data.
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ABSTRACT:
SUBMITTER: Wang Y
PROVIDER: S-EPMC4957112 | biostudies-literature | 2016 Jul
REPOSITORIES: biostudies-literature
Publications
Random Bits Forest: a Strong Classifier/Regressor for Big Data.
Wang Yi Y Li Yi Y Pu Weilin W Wen Kathryn K Shugart Yin Yao YY Xiong Momiao M Jin Li L
Scientific reports 20160722
Efficiency, memory consumption, and robustness are common problems with many popular methods for data analysis. As a solution, we present Random Bits Forest (RBF), a classification and regression algorithm that integrates neural networks (for depth), boosting (for width), and random forests (for prediction accuracy). Through a gradient boosting scheme, it first generates and selects ~10,000 small, 3-layer random neural networks. These networks are then fed into a modified random forest algorithm ...[more]
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