- Use of Randomization to Normalize Feature Merits S.J. Hong, J. Hosking, and S. Winograd
- Partitioning Nominal Attributes in Decision Trees D. Coppersmith, S.J. Hong, and J. Hosking
- Learning from Identifier Attributes: Distribution-Based Aggregation for Relational
- A MACHINE-LEARNING APPROACH TO OPTIMAL BID PRICING
- Approaching the ILP 2005 Challenge: Class-Conditional Bayesian Propositionalization for
- Empirical Evaluation of a Dynamic Experiment Design Method for Prediction of MHC Class I-Binding Peptides1
- Decision-Rule Solutions for Data Mining with Missing Sholom Weiss and Nitin Indurkhya
- Attribute Selection for Modeling I. Kononenko and S.J. Hong
- Decomposition of Heterogeneous Classification C. Apte, S.J. Hong, J. Hosking, J. Lepre, E. Pednault,
- ROC Confidence Bands: An Empirical Evaluation Sofus A. Macskassy SMACSKAS@STERN.NYU.EDU
- Operational Data Analysis: Improved Predictions Using Multi-Computer Pattern Detection
- Error Limiting Reductions Between Classification Tasks Alina Beygelzimer beygel@us.ibm.com
- RMINI:An Iterative Approach for Generating Minimal Rules from Examples
- Solving Regression Problems with Rule-Based Ensemble Classifiers
- DOI: 10.1007/s00453-003-1038-1 Algorithmica (2003) 37: 263293
- Sparsity and smoothness via the fused lasso Robert Tibshirani, Michael Saunders,
- Use of Contextual Information for Feature Ranking and Discretization
- RAMP: Rules Abstraction for Modeling and C. Apte, S.J. Hong, J. Lepre, S. Prasad, and B. Rosen
- Predicting Equity Returns from Securities Data C. Apte and S.J. Hong
- Tracking Curved Regularized Optimization Solution Paths
- Margin Maximizing Loss Functions Saharon Rosset, Ji Zhu and Trevor Hastie
- Ranking-Based Evaluation of Regression Models Saharon Rosset, Claudia Perlich, Bianca Zadrozny
- Robust Boosting and its Relation to Bagging Saharon Rosset
- Abstract--We describe a grid-based approach for enterprise-scale data mining that leverages database technology for I/O
- Engineering Applications of Artificial Intelligence ] (]]]]) ]]]]]] Empirical evaluation of feature subset selection based on a real-world
- Learning and Evaluating Classifiers under Sample Selection Bias Bianca Zadrozny zadrozny@us.ibm.com
- Integrating Customer Value Considerations into Predictive Modeling Saharon Rosset, Einat Neumann
- Knowledge-Based Data Mining Sholom M. Weiss, Stephen J. Buckley, Shubir Kapoor, and Sren Damgaard
- Data Intensive Analytics for Predictive Modeling C. Apte, S.J. Hong, R. Natarajan, E.P.D. Pednault, F. Tipu, S.M. Weiss
- Predictive algorithms in the management
- Automated generation of model cases for
- A System for Real-time Competitive Market Intelligence Sholom M. Weiss and Naval K. Verma
- RC 21982 (98791) 8 March 2001 Computer Science IBM Research Report
- Using Simulated Pseudo Data To Speed Up Statistical Predictive Modeling From Massive Data Sets
- Active Learning Using Adaptive Resampling Vijay Iyengar, Chid Apte, and Tong Zhang
- Lightweight Rule Induction Sholom Weiss and Nitin Indurkhya
- RC 21907 (98532) 7 December 2000 Computer Science IBM Research Report
- Lightweight Document Clustering Sholom Weiss, Brian White, Chid Apte
- D A T A M I N I N G Lightweight Document
- I N T E L L I G E N T I N F O R M A T I O N R E T R I E V A L Maximizing Text-Mining
- RC 21314 (94531) 31MAR98 Computer Science/Mathematics Research Report
- Data Mining: Guest Editorial Future Generation Computer Systems
- Data Mining with Decision Trees and Decision Rules C. Apte and S.M. Weiss
- Automated Learning of Decision Rules for Text Categorization
- Predicting Defects in Disk Drive Manufacturing: A Case Study in High-Dimensional Classification
- -norm Support Vector Machines Ji Zhu, Saharon Rosset, Trevor Hastie, Rob Tibshirani
- In many problem domains, high-cost outcomes often have low probabilities of occurrence.
- Data Mining -An Industrial Research Perspective IEEE Computational Science and Engineering
- Business Applications of Data Mining Chidanand Apte, Bing Liu, Edwin P.D. Pednault, Padhraic Smyth
- Towards Language Independent Automated Learning of Text Categorization Models
- Multi-Relational Learning for Genetic Data: Issues and Claudia Perlich
- Journal of Machine Learning Research 5 (2004) 941973 Submitted 5/03; Revised 10/03; Published 8/04 Boosting as a Regularized Path
- ARTICLE IN PRESS Computers in Biology and Medicine ( )
- Text Mining with Decision Trees and Decision Rules C. Apte, F. Damerau, and S.M. Weiss
- Estimating Performance Gains for Voted Decision N. Indurkhya and S.M. Weiss
- As owners of cars, homes, and other property, consumers buy property and casualty insurance to protect themselves
- RC 22393 (W0204-041) 4/9/2002 Mathematics 14 pages
- Journal of Machine Learning Research 0 (2004) 124 Submitted 3/04; Published ?? The Entire Regularization Path for the Support Vector
- Electronic Commerce Research, 5: 7598 (2005) 2005 Springer Science + Business Media, Inc. Manufactured in the Netherlands.
- Statistical Learning Theory E.P.D. Pednault
- Data Mining with Extended Symbolic Models C. Apte, E. Pednault, and S.M. Weiss
- Advances in Predictive Models for Data Mining Se June Hong and Sholom Weiss
- A Statistical Perspective on Data Mining J. Hosking, E. Pednault, and M. Sudan
- A probabilistic estimation framework
- Transform Regression and the Kolmogorov Superposition Theorem
- Data Mining Analytics for Business Intelligence and Decision Support Chid Apte, T.J. Watson Research Center, IBM Research Division
- Experiments in High-Dimensional Text Categorization Fred J. Damerau, Tong Zhang, Sholom M. Weiss and Nitin Indurkhya
- One-Benefit learning: Cost-sensitive learning with restricted cost information
- Case Studies in High-Dimensional Classification C. Apte, R. Sasisekharan, V. Seshadri, and S.M. Weiss
- IBM Research Report RC-21483 Probabilistic Estimation Based Data Mining for Discovering
- Lightweight Collaborative Filtering Method for Binary Encoded Data
