Volume 7, Issue sup2, July 2014, Pages 35 - 43
Adaptive generalized ensemble construction with feature selection and its application in recommendation
- Jin Tian, Nan Feng
- Corresponding Author
- Jin Tian
Available Online 9 January 2017.
- https://doi.org/10.1080/18756891.2014.947111How to use a DOI?
- Ensemble learning, Feature selection, Coevolution, Recommendation
- This paper presents an adaptive generalized ensemble method with refined feature selection strategy and self-adjusted mechanism for ensemble size. The coevolutionary algorithm is introduced to optimize the ensemble and the feature weighting. There are two stages in the proposed method. In the coevolutionary stage, a component network corresponds to a subpopulation and the feature set is designed in another subpopulation. All subpopulations are coevolved simultaneously. Moreover, the study on the ensemble size is conducted in the structure refining stage. Finally, we apply the proposed approach to a recommendation task. Experimental results indicate that the proposed algorithm can achieve good classification performance, small feature subsets and compact ensemble structure.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Jin Tian AU - Nan Feng PY - 2017 DA - 2017/01 TI - Adaptive generalized ensemble construction with feature selection and its application in recommendation JO - International Journal of Computational Intelligence Systems SP - 35 EP - 43 VL - 7 IS - sup2 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2014.947111 DO - https://doi.org/10.1080/18756891.2014.947111 ID - Tian2017 ER -