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Full-Text Articles in Physical Sciences and Mathematics
A Pseudo Nearest-Neighbor Approach For Missing Data Recovery On Gaussian Random Data Sets, Xiaolu Huang, Qiuming Zhu
A Pseudo Nearest-Neighbor Approach For Missing Data Recovery On Gaussian Random Data Sets, Xiaolu Huang, Qiuming Zhu
Computer Science Faculty Publications
Missing data handling is an important preparation step for most data discrimination or mining tasks. Inappropriate treatment of missing data may cause large errors or false results. In this paper, we study the effect of a missing data recovery method, namely the pseudo- nearest neighbor substitution approach, on Gaussian distributed data sets that represent typical cases in data discrimination and data mining applications. The error rate of the proposed recovery method is evaluated by comparing the clustering results of the recovered data sets to the clustering results obtained on the originally complete data sets. The results are also compared with …
An Iterative Initial-Points Refinement Algorithm For Categorical Data Clustering, Ying Sun, Qiuming Zhu, Zhengxin Chen
An Iterative Initial-Points Refinement Algorithm For Categorical Data Clustering, Ying Sun, Qiuming Zhu, Zhengxin Chen
Computer Science Faculty Publications
The original k-means clustering algorithm is designed to work primarily on numeric data sets. This prohibits the algorithm from being directly applied to categorical data clustering in many data mining applications. The k-modes algorithm [Z. Huang, Clustering large data sets with mixed numeric and categorical value, in: Proceedings of the First Pacific Asia Knowledge Discovery and Data Mining Conference. World Scientific, Singapore, 1997, pp. 21–34] extended the k-means paradigm to cluster categorical data by using a frequency-based method to update the cluster modes versus the k-means fashion of minimizing a numerically valued cost. However, as is …
Studying The Functional Genomics Of Stress Responses In Loblolly Pine With The Expresso Microarray Experiment Management System, Lenwood S. Heath, Naren Ramakrishnan, Ronald R. Sederoff, Ross W. Whetten, Boris I. Chevone, Craig Struble, Vincent Y. Jouenne, Dawei Chen, Leonel Van Zyl, Ruth Grene
Studying The Functional Genomics Of Stress Responses In Loblolly Pine With The Expresso Microarray Experiment Management System, Lenwood S. Heath, Naren Ramakrishnan, Ronald R. Sederoff, Ross W. Whetten, Boris I. Chevone, Craig Struble, Vincent Y. Jouenne, Dawei Chen, Leonel Van Zyl, Ruth Grene
Mathematics, Statistics and Computer Science Faculty Research and Publications
Conception, design, and implementation of cDNA microarray experiments present a variety of bioinformatics challenges for biologists and computational scientists. The multiple stages of data acquisition and analysis have motivated the design of Expresso, a system for microarray experiment management. Salient aspects of Expresso include support for clone replication and randomized placement; automatic gridding, extraction of expression data from each spot, and quality monitoring; flexible methods of combining data from individual spots into information about clones and functional categories; and the use of inductive logic programming for higher-level data analysis and mining. The development of Expresso is occurring in parallel with …