Selecting the Right Correlation Measure for Binary Data
暂无分享,去创建一个
Yanchi Liu | William Nick Street | Lian Duan | Songhua Xu | Yi-fang Brook Wu | Yanchi Liu | Songhua Xu | Y. Wu | Lian Duan | W. Street
[1] Joan Feigenbaum,et al. Finding highly correlated pairs efficiently with powerful pruning , 2006, CIKM '06.
[2] Frederick Mosteller,et al. Association and Estimation in Contingency Tables , 1968 .
[3] Yiyu Yao,et al. Peculiarity Oriented Multi-database Mining , 1999, PKDD.
[4] A. Bate,et al. A Bayesian neural network method for adverse drug reaction signal generation , 1998, European Journal of Clinical Pharmacology.
[5] William Nick Street,et al. Finding Maximal Fully-Correlated Itemsets in Large Databases , 2009, 2009 Ninth IEEE International Conference on Data Mining.
[6] Charles E. Heckler,et al. Applied Multivariate Statistical Analysis , 2005, Technometrics.
[7] Hui Xiong,et al. TOP-COP: Mining TOP-K Strongly Correlated Pairs in Large Databases , 2006, Sixth International Conference on Data Mining (ICDM'06).
[8] M. Newman,et al. Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[9] Tomasz Imielinski,et al. Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.
[10] H. Everett. "Relative State" Formulation of Quantum Mechanics , 1957 .
[11] Chris Jermaine,et al. Finding the most interesting correlations in a database: how hard can it be? , 2005, Inf. Syst..
[12] Jiawei Han,et al. ACM Transactions on Knowledge Discovery from Data: Introduction , 2007 .
[13] G. Niklas Norén,et al. Temporal pattern discovery for trends and transient effects: its application to patient records , 2008, KDD.
[14] Christophe G. Giraud-Carrier,et al. Behavior-based clustering and analysis of interestingness measures for association rule mining , 2014, Data Mining and Knowledge Discovery.
[15] Edward Omiecinski,et al. Alternative Interest Measures for Mining Associations in Databases , 2003, IEEE Trans. Knowl. Data Eng..
[16] C. Garvan,et al. Proportions, odds, and risk. , 2004, Radiology.
[17] Gregory Piatetsky-Shapiro,et al. Discovery, Analysis, and Presentation of Strong Rules , 1991, Knowledge Discovery in Databases.
[18] Yanchi Liu,et al. Speeding up correlation search for binary data , 2013, Pattern Recognit. Lett..
[19] H. T. Reynolds,et al. The analysis of cross-classifications , 1977 .
[20] Hua Xu,et al. Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records , 2013, J. Am. Medical Informatics Assoc..
[21] Vipin Kumar,et al. Introduction to Data Mining , 2022, Data Mining and Machine Learning Applications.
[22] Ted Dunning,et al. Accurate Methods for the Statistics of Surprise and Coincidence , 1993, CL.
[23] Vipin Kumar,et al. Introduction to Data Mining, (First Edition) , 2005 .
[24] William DuMouchel,et al. Bayesian Data Mining in Large Frequency Tables, with an Application to the FDA Spontaneous Reporting System , 1999 .
[25] Jaideep Srivastava,et al. Selecting the right objective measure for association analysis , 2004, Inf. Syst..
[26] Howard J. Hamilton,et al. Interestingness measures for data mining: A survey , 2006, CSUR.
[27] Ning Zhong,et al. Dynamically Organizing KDD Processes , 2001, Int. J. Pattern Recognit. Artif. Intell..
[28] Pang-Ning Tan,et al. Interestingness Measures for Association Patterns : A Perspective , 2000, KDD 2000.
[29] Hui Xiong,et al. TAPER: a two-step approach for all-strong-pairs correlation query in large databases , 2006, IEEE Transactions on Knowledge and Data Engineering.
[30] Yanchi Liu,et al. Community detection in graphs through correlation , 2014, KDD.
[31] Rajeev Motwani,et al. Beyond market baskets: generalizing association rules to correlations , 1997, SIGMOD '97.
[32] Rajeev Motwani,et al. Dynamic itemset counting and implication rules for market basket data , 1997, SIGMOD '97.