- 42 November 1996/Vol. 39, No. 11 COMMUNICATIONS OF THE ACM THE AMOUNT OF DATA COLLECTED AND WAREHOUSED IN ALL INDUSTRIES IS GROWING AT
- Data Mining: Statistics and More? David J. HAND
- A Combinatorial Fusion Method for Feature Mining Ye Tian Gary Weiss D. Frank Hsu Qiang Ma
- Appears in Proceedings of the 4 International Conference on Knowledge Discovery and Data Mining,
- Machine Learning, 15, 201-221 (1994) 1994 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
- To appear in W. Kloesgen and J. Zytkow (eds.), Handbook of Knowledge Discovery and Data Mining, Oxford University Press.
- Link Mining: A New Data Mining Challenge Lise Getoor
- UBDM 2006: Utility-Based Data Mining 2006 Workshop Report
- Wrapper-based Computation and Evaluation of Sampling Methods for Imbalanced Datasets
- Toward Economic Machine Learning and Utility-based Data Mining
- Machine Learning 1: 81-106, 1986 1986 Kluwer Academic Publishers, Boston -Manufactured in TheNetherlands
- October 2008 Rev 4 1/42 MEMS motion sensor
- Activity Recognition using Cell Phone Accelerometers Jennifer R. Kwapisz, Gary M. Weiss, Samuel A. Moore
- A Combinatorial Fusion Method for Feature Construction , Gary M. Weiss2
- A Quantitative Study of Small Disjuncts Gary M. Weiss
- Learning to Predict Extremely Rare Events Gary M. Weiss*
- International Journal of Information Technology & Decision Making Vol. 5, No. 4 (2006) 597604
- Utility based Data Mining for Time Series Analysis -Cost-sensitive Learning for Neural Network Predictors
- Using Rules in Object-Oriented Designs Daniel Dvorak
- Are Decision Trees Always Greener on the Open (Source) Side of the Fence?
- A Multiple Resampling Method for Learning from Imbalanced Data Sets Andrew Estabrooks Taeho Jo and Nathalie Japkowicz
- Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?
- DATA MINING IN TELECOMMUNICATIONS Gary M. Weiss
- Maximizing Classifier Utility when Training Data is Costly Gary M. Weiss and Ye Tian
- Machine Learning Paradigms for Utility-based Data Mining IBM T. J. Watson Research Center
- Appears in Proceedings of the 12 International Conference on Machine Learning,
- Appears in Proceedings of the 15 International Conference on Machine Learning,
- Bosch Sensortec Digital, triaxal acceleration sensor
- Department of Computer Science, University of Waikato, New Zealand
- Data Mining in the Real World: Experiences, Challenges, and Recommendations
- 486 Section: Service Data Mining in the Telecommunications
- Abstract--Mobile devices are becoming increasingly sophisti-cated and now incorporate many diverse and powerful sensors.
- Economical Active Feature-value Acquisition through Expected Utility Estimation
- Technical Report ML-TR-44, Department of Computer Science, Rutgers University August 2, 2001
- Department of Computer Science, University of Waikato, New Zealand
- Active Learning using Adaptive Resampling Vijay S. Iyengar
- Appears in Proceedings of the Tenth Conference on Innovative Applications of Artificial Intelligence, AAAI Press, 1998, 1087-1093
- The Impact of Small Disjuncts on Classifier Gary M. Weiss
- Data Min Knowl Disc DOI 10.1007/s10618-007-0082-x
- Appears in the Journal of Object-Oriented Programming, 11(7): 25-35, SIGS Publication Inc., Nov/Dec 1998. Gary M. Weiss and Johannes P. Ros
- Encyclopedia of Data Warehousing and
- MINING WITH RARE CASES Gary M. Weiss
- Appears in Knowledge-Based Intelligent Techniques in Industry (chapter 8), L. C. Jain, editor, CRC Press, 249-275, 1998.
- First International Workshop on
- Report on UBDM-05: Workshop on Utility-Based Data Mining Computer and Information Science Dept.
- A Quantitative Study of Small Disjuncts: Experiments and Results
- Timeweaver: a Genetic Algorithm for Identifying Predictive Patterns in Sequences of Events
- A Semi-Supervised Approach for Web Spam Detection using Combinatorial Feature-Fusion
- Appears in the Proceedings of the Second ACM SIGKDD Workshop on Utility-Based Data Mining, ACM Press, 3-11, August 20, 2006.
- Does Cost-Sensitive Learning Beat Sampling for Classifying Rare Classes?
- Mining Predictive Patterns in Sequences of Events Gary M. Weiss
- Presented at the 1998 NIPS-98 Workshop on Learning from Ambiguous and Complex Examples. Event Prediction: Learning from Ambiguous Examples
- Stand-By Depends-On TICKETALERT
- Improving Classifier Utility by Altering the Misclassification Cost Ratio
- Contextual Recommender Problems [Extended Abstract]
- Get Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers
- Trust No One: Evaluating Trust-based Filtering for Recommenders John O'Donovan, Barry Smyth
- On Active Learning for Data Acquisition Zhiqiang Zheng and Balaji Padmanabhan
- Active Sampling for Class Probability Estimation and Ranking Maytal Saar-Tsechansky MAYTAL.SAAR-TSECHANSKY@BUS.UTEXAS.EDU
- Journal of Machine Learning Research 2 (2002) 397-418 Submitted 2/01; Published 2/02 The Learning-Curve Sampling Method Applied to
- Active Sampling for Feature Selection Sriharsha Veeramachaneni and Paolo Avesani
- Heterogeneous Uncertainty Sampling for Supervised Learning David D. Lewis and Jason Catlett
- THE EFFECT OF SMALL DISJUNCTS AND CLASS DISTRIBUTION ON DECISION TREE LEARNING
- Quantification and Semi-Supervised Classification Methods for Handling Changes in Class Distribution
- Sigkdd Explorations. Volume 6, Issue 1 -Page 7 Mining with Rarity: A Unifying Framework
- Identifying User Traits by Mining Smart Phone Accelerometer Data
- Design Considerations for the WISDM Smart Phone-based Sensor Mining Architecture
