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» Mining Compressed Frequent-Pattern Sets
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ACSC
2005
IEEE
14 years 2 months ago
The Electronic Primaries: Predicting the U.S. Presidency Using Feature Selection with Safe Data Reduction
The data mining inspired problem of finding the critical, and most useful features to be used to classify a data set, and construct rules to predict the class of future examples ...
Pablo Moscato, Luke Mathieson, Alexandre Mendes, R...
SIGKDD
2010
151views more  SIGKDD 2010»
13 years 3 months ago
Limitations of matrix completion via trace norm minimization
In recent years, compressive sensing attracts intensive attentions in the field of statistics, automatic control, data mining and machine learning. It assumes the sparsity of the ...
Xiaoxiao Shi, Philip S. Yu
KDD
2009
ACM
189views Data Mining» more  KDD 2009»
14 years 3 months ago
CoCo: coding cost for parameter-free outlier detection
How can we automatically spot all outstanding observations in a data set? This question arises in a large variety of applications, e.g. in economy, biology and medicine. Existing ...
Christian Böhm, Katrin Haegler, Nikola S. M&u...
ICDM
2005
IEEE
135views Data Mining» more  ICDM 2005»
14 years 2 months ago
Bit Reduction Support Vector Machine
Abstract— Support vector machines are very accurate classifiers and have been widely used in many applications. However, the training and to a lesser extent prediction time of s...
Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, And...
ICDM
2008
IEEE
96views Data Mining» more  ICDM 2008»
14 years 3 months ago
Filling in the Blanks - Krimp Minimisation for Missing Data
Many data sets are incomplete. For correct analysis of such data, one can either use algorithms that are designed to handle missing data or use imputation. Imputation has the bene...
Jilles Vreeken, Arno Siebes