相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Enabling Smart Data: Noise filtering in Big Data classification
Diego Garcia-Gil et al.
INFORMATION SCIENCES (2019)
Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce
Sergio Ramirez-Gallego et al.
INFORMATION FUSION (2018)
Principal Components Analysis Random Discretization Ensemble for Big Data
Diego Garcia-Gil et al.
KNOWLEDGE-BASED SYSTEMS (2018)
A distributed evolutionary multivariate discretizer for Big Data processing on Apache Spark
S. Ramirez-Gallego et al.
SWARM AND EVOLUTIONARY COMPUTATION (2018)
A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment
Jianguo Chen et al.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2017)
Ensemble learning for data stream analysis: A survey
Bartosz Krawczyk et al.
INFORMATION FUSION (2017)
Learning distributed discrete Bayesian Network Classifiers under MapReduce with Apache Spark
Jacinto Arias et al.
KNOWLEDGE-BASED SYSTEMS (2017)
kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data
Jesus Maillo et al.
KNOWLEDGE-BASED SYSTEMS (2017)
Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark
Sergio Ramirez-Gallego et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS (2017)
MR-DIS: democratic instance selection for big data by MapReduce
Alvar Arnaiz-Gonzalez et al.
PROGRESS IN ARTIFICIAL INTELLIGENCE (2017)
Large-scale multi-label ensemble learning on Spark
Jorge Gonzalez-Lopez et al.
2017 16TH IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS / 11TH IEEE INTERNATIONAL CONFERENCE ON BIG DATA SCIENCE AND ENGINEERING / 14TH IEEE INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS (2017)
An insight into imbalanced Big Data classification: outcomes and challenges
Alberto Fernandez et al.
COMPLEX & INTELLIGENT SYSTEMS (2017)
Social big data: Recent achievements and new challenges
Gema Bello-Orgaz et al.
INFORMATION FUSION (2016)
Instance selection of linear complexity for big data
Alvar Arnaiz-Gonzalez et al.
KNOWLEDGE-BASED SYSTEMS (2016)
Diversity techniques improve the performance of the best imbalance learning ensembles
Jose F. Diez-Pastor et al.
INFORMATION SCIENCES (2015)
The rise of big data on cloud computing: Review and open research issues
Ibrahim Abaker Targio Hashem et al.
INFORMATION SYSTEMS (2015)
A Bayesian approach for comparing cross-validated algorithms on multiple data sets
Giorgio Corani et al.
MACHINE LEARNING (2015)
Big Data: A Survey
Min Chen et al.
MOBILE NETWORKS & APPLICATIONS (2014)
Democratic instance selection: A linear complexity instance selection algorithm based on classifier ensemble concepts
Cesar Garcia-Osorio et al.
ARTIFICIAL INTELLIGENCE (2010)
PLANET: Massively Parallel Learning of Tree Ensembles with MapReduce
Biswanath Panda et al.
PROCEEDINGS OF THE VLDB ENDOWMENT (2009)
Mapreduce: Simplified data processing on large clusters
Jeffrey Dean et al.
COMMUNICATIONS OF THE ACM (2008)
RotBoost: A technique for combining Rotation Forest and AdaBoost
Chun-Xia Zhang et al.
PATTERN RECOGNITION LETTERS (2008)
Rotation forest:: A new classifier ensemble method
Juan J. Rodriguez et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2006)
分享论文
