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Statistical Analysis and Data Mining, Volume 4
Volume 4, Number 1, February 2011
- Joseph S. Verducci:
In this issue. 1-2
- Arnold Goodman:
Emerging topics and challenges for statistical analysis and data mining. 3-8 - James Goodnight:
The forecast for predictive analytics: hot and getting hotter. 9-10
- Xin Jin, Sangkyum Kim, Jiawei Han, Liangliang Cao, Zhijun Yin:
A general framework for efficient clustering of large datasets based on activity detection. 11-29 - Hoyt A. Koepke, Bertrand S. Clarke:
On the limits of clustering in high dimensions via cost functions. 30-53 - Hongjun Wang, Hanhuai Shan, Arindam Banerjee:
Bayesian cluster ensembles. 54-70 - Adelaide Freitas
, Vera Afreixo
Improving the performance of the iterative signature algorithm for the identification of relevant patterns. 71-83 - Jia Li:
Agglomerative connectivity constrained clustering for image segmentation. 84-99 - Fuzhen Zhuang, Ping Luo
Exploiting associations between word clusters and document classes for cross-domain text categorization. 100-114 - Hemant Ishwaran
Random survival forests for high-dimensional data. 115-132 - Montserrat Fuentes, Bowei Xi, William S. Cleveland:
Trellis display for modeling data from designed experiments. 133-145
Volume 4, Number 2, April 2011
- Lynne Billard:
In this issue. 147-148
- Lynne Billard:
Brief overview of symbolic data and analytic issues. 149-156 - Monique Noirhomme-Fraiture, Paula Brito
Far beyond the classical data models: symbolic data analysis. 157-170 - Paola Zuccolotto
Symbolic missing data imputation in principal component analysis. 171-183 - Manabu Ichino:
The quantile method for symbolic principal component analysis. 184-198 - Simona Korenjak-Cerne, Vladimir Batagelj
Clustering large data sets described with discrete distributions and its application on TIMSS data set. 199-215 - Javier Arroyo
Smoothing methods for histogram-valued time series: an application to value-at-risk. 216-228 - Ahlame Douzal Chouakria, Lynne Billard, Edwin Diday:
Principal component analysis for interval-valued observations. 229-246
Volume 4, Number 3, June 2011
- Amy Braverman, Noel Cressie
A likelihood-based comparison of temporal models for physical processes. 247-258 - Alan J. Izenman, Philip W. Harris, Jeremy Mennis, Joseph Jupin, Zoran Obradovic:
Local spatial biclustering and prediction of urban juvenile delinquency and recidivism. 259-275 - Vandana Pursnani Janeja, Aryya Gangopadhyay, Seyed H. Mohammadi, Revathi Palanisamy:
Discovery of anomalous spatio-temporal windows using discretized spatio-temporal scan statistics. 276-300 - Yulan Liang, Arpad Kelemen:
Sequential support vector regression with embedded entropy for SNP selection and disease classification. 301-312
- Alexandre Plastino, Richard Fuchshuber, Simone L. Martins, Alex Alves Freitas, Saïd Salhi
A hybrid data mining metaheuristic for the p-median problem. 313-335
- Kanishka Bhaduri, Kamalika Das, Kirk D. Borne, Chris Giannella, Tushar Mahule, Hillol Kargupta:
Scalable, asynchronous, distributed eigen monitoring of astronomy data streams. 336-352
- Arnold Goodman:
Erratum: Emerging Topics and Challenges for Statistical Analysis and Data Mining. 353
Volume 4, Number 4, August 2011
- Ashok N. Srivastava, Nitesh V. Chawla
Special issue on the best papers of the Conference on Intelligent Data Understanding (CIDU 2010). 355-357 - Goo Jun
Spatially adaptive semi-supervised learning with Gaussian processes for hyperspectral data analysis. 358-371 - Claire Monteleoni
Tracking climate models. 372-392 - Kamalika Das, Kanishka Bhaduri, Petr Votava:
Distributed anomaly detection using 1-class SVM for vertically partitioned data. 393-406 - Amy McGovern, David John Gagne II
Using spatiotemporal relational random forests to improve our understanding of severe weather processes. 407-429 - Varun Chandola, Ranga Raju Vatsavai
A scalable gaussian process analysis algorithm for biomass monitoring. 430-445 - Anthony M. D'Amato, Aaron J. Ridley
Retrospective-cost-based adaptive model refinement for the ionosphere and thermosphere. 446-458
Volume 4, Number 5, October 2011
- Douglas L. Steinley, Stanley Wasserman:
Introduction: special issue of statistical analysis and data mining on networks. 459-460 - Edoardo M. Airoldi
Confidence sets for network structure. 461-469 - Vladimir Ouzienko, Yuhong Guo, Zoran Obradovic:
A decoupled exponential random graph model for prediction of structure and attributes in temporal social networks. 470-486 - Douglas L. Steinley, Michael J. Brusco, Stanley Wasserman:
Clusterwise p* models for social network analysis. 487-496 - Karsten Steinhaeuser, Nitesh V. Chawla
Complex networks as a unified framework for descriptive analysis and predictive modeling in climate science. 497-511
- Michele Coscia, Fosca Giannotti, Dino Pedreschi
A classification for community discovery methods in complex networks. 512-546
- Laura Dabbish, W. Ben Towne, Jana Diesner, James D. Herbsleb
Construction of association networks from communication in teams working on complex projects. 547-563
Volume 4, Number 6, December 2011
- Joseph S. Verducci, Hernando Ombao:
Introduction to the special issue on best papers from the SLDM competition. 565-566 - Wei-Chen Chen, Ranjan Maitra
Model-based clustering of regression time series data via APECM - an AECM algorithm sung to an even faster beat. 567-578 - Anna J. Blackstock, Amita K. Manatunga, Youngja Park
Clustering based on periodicity in high-throughput time course data. 579-589 - Georg M. Goerg:
A nonparametric frequency domain EM algorithm for time series classification with applications to spike sorting and macro-economics. 590-603 - Shuo Chen, F. DuBois Bowman:
A novel support vector classifier for longitudinal high-dimensional data and its application to neuroimaging data. 604-611 - Ashin Mukherjee, Ji Zhu:
Reduced rank ridge regression and its kernel extensions. 612-622
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