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ICDM
2007
IEEE
97views Data Mining» more  ICDM 2007»
16 years 1 months ago
Supervised Learning by Training on Aggregate Outputs
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....
ICDM
2007
IEEE
136views Data Mining» more  ICDM 2007»
16 years 1 months ago
Dynamic Micro Targeting: Fitness-Based Approach to Predicting Individual Preferences
It is crucial to segment customers intelligently in order to offer more targeted and personalized products and services. Traditionally, customer segmentation is achieved using sta...
Tianyi Jiang, Alexander Tuzhilin
AUSDM
2007
Springer
145views Data Mining» more  AUSDM 2007»
16 years 1 months ago
Temporal Pattern Matching for the Prediction of Stock Prices
Time series data poses a significant variation to the traditional segmentation techniques of data mining because the observation is derived from multiple instances of the same und...
Richi Nayak, Paul te Braak
ICDM
2006
IEEE
89views Data Mining» more  ICDM 2006»
16 years 1 months ago
On the Lower Bound of Local Optimums in K-Means Algorithm
The k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. However, ...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung
ICDM
2006
IEEE
193views Data Mining» more  ICDM 2006»
16 years 1 months ago
Feature Subset Selection on Multivariate Time Series with Extremely Large Spatial Features
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
Hyunjin Yoon, Cyrus Shahabi