Efficient Feature Selection Framework for Digital Marketing Applications
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Wei Zhang | Said Kobeissi | Scott Tomko | Chris Challis | Shiladitya Bose | Wei Zhang | Shiladitya Bose | Chris Challis | Said Kobeissi | Scott Tomko
[1] Yungho Leu,et al. A novel hybrid feature selection method for microarray data analysis , 2011, Appl. Soft Comput..
[2] Paul R. Kroeger. Analyzing Grammar: Frontmatter , 2005 .
[3] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[4] Kari Torkkola,et al. Feature Extraction by Non-Parametric Mutual Information Maximization , 2003, J. Mach. Learn. Res..
[5] Fuhui Long,et al. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy , 2003, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] Huan Liu,et al. Unsupervised Feature Selection for Multi-View Data in Social Media , 2013, SDM.
[7] Bhanukiran Vinzamuri,et al. Feature Grouping Using Weighted l1 Norm for High-Dimensional Data , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).
[8] Andrew Stranieri,et al. Hybrid Wrapper-Filter Approaches for Input Feature Selection Using Maximum Relevance and Artificial Neural Network Input Gain Measurement Approximation (ANNIGMA) , 2010, 2010 Fourth International Conference on Network and System Security.
[9] Lei Yu,et al. Fast Correlation Based Filter (FCBF) with a different search strategy , 2008, 2008 23rd International Symposium on Computer and Information Sciences.
[10] Hui-Huang Hsu,et al. Hybrid feature selection by combining filters and wrappers , 2011, Expert Syst. Appl..
[11] S B Kotsiantis,et al. RETRACTED ARTICLE: Feature selection for machine learning classification problems: a recent overview , 2014, Artificial Intelligence Review.
[12] P. Kroeger. Analyzing Grammar: An Introduction , 2005 .
[13] Vipin Kumar,et al. Feature Selection: A literature Review , 2014, Smart Comput. Rev..
[14] Mohamed S. Kamel,et al. An Efficient Greedy Method for Unsupervised Feature Selection , 2011, 2011 IEEE 11th International Conference on Data Mining.
[15] Jos'e R. Berrendero,et al. The mRMR variable selection method: a comparative study for functional data , 2015, 1507.03496.
[16] Andrew Stranieri,et al. Hybrid Wrapper-filter Aapproaches for Input Feature Selection using Maximum relevance-Minimum redundancy and Artificial Neural Network Input Gain Measurement Approximation (ANNIGMA) , 2011, ACSC.
[17] James Bailey,et al. Effective global approaches for mutual information based feature selection , 2014, KDD.
[18] Jie Hu,et al. Research of new strategies for improving CBR system , 2012, Artificial Intelligence Review.
[19] Sethuraman Panchanathan,et al. Efficient Approximate Solutions to Mutual Information Based Global Feature Selection , 2015, 2015 IEEE International Conference on Data Mining.
[20] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[21] Paul R. Kroeger,et al. Analyzing Grammar: List of abbreviations , 2005 .
[22] Karthik Thyagarajan Iyer. Computational complexity of data mining algorithms used in fraud detection , 2015 .
[23] Philip S. Yu,et al. Online Unsupervised Multi-view Feature Selection , 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).
[24] Ying Cui,et al. Convex Principal Feature Selection , 2010, SDM.
[25] Huan Liu,et al. Feature selection for classification: A review , 2014 .
[26] Kan Deng,et al. Omega: on-line memory-based general purpose system classifier , 1999 .