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» A Partial-Repeatability Approach to Data Mining
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KDD
2010
ACM
224views Data Mining» more  KDD 2010»
14 years 1 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
14 years 1 months ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
PAKDD
2010
ACM
167views Data Mining» more  PAKDD 2010»
14 years 1 months ago
Resource-Bounded Information Extraction: Acquiring Missing Feature Values on Demand
We present a general framework for the task of extracting specific information “on demand” from a large corpus such as the Web under resource-constraints. Given a database wit...
Pallika Kanani, Andrew McCallum, Shaohan Hu
ECML
2005
Springer
13 years 12 months ago
Clustering and Metaclustering with Nonnegative Matrix Decompositions
Although very widely used in unsupervised data mining, most clustering methods are affected by the instability of the resulting clusters w.r.t. the initialization of the algorithm ...
Liviu Badea
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
13 years 11 months ago
Feature Selection for Nonlinear Kernel Support Vector Machines
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
Olvi L. Mangasarian, Gang Kou