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| Authors: | Miron B. Kursa | ||||||
| Title: | rFerns: An Implementation of the Random Ferns Method for General-Purpose Machine Learning | ||||||
| Abstract: | Random ferns is a very simple yet powerful classification method originally introduced for specific computer vision tasks. In this paper, I show that this algorithm may be considered as a constrained decision tree ensemble and use this interpretation to introduce a series of modifications which enable the use of random ferns in general machine learning problems. Moreover, I extend the method with an internal error approximation and an attribute importance measure based on corresponding features of the random forest algorithm. I also present the R package rFerns containing an efficient implementation of this modified version of random ferns. | ||||||
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Page views:: 3488. Submitted: 2012-03-01. Published: 2014-11-13. |
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| Paper: |
rFerns: An Implementation of the Random Ferns Method for General-Purpose Machine Learning
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| DOI: |
10.18637/jss.v061.i10
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This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. |