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» Predicting Time Series with Support Vector Machines
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SCAI
2008
15 years 4 months ago
Defect Prediction in Hot Strip Rolling Using ANN and SVM
One of the largest factors affecting the loss for steel manufacturing are defects in the steel strips produced. Therefore the prediction of these defects forehand would be very im...
Manu Hietaniemi, Ulla Elsilä, Perttu Laurinen...
111
Voted
ICDM
2006
IEEE
140views Data Mining» more  ICDM 2006»
15 years 9 months ago
Mining the Future: Predicting Itemsets' Support of Association Rules Mining
This paper proposes a novel research dimension in the field of data mining, which is mining the future data before its arrival, or in other words: predicting association rules ahe...
Shenoda Guirguis, Khalil M. Ahmed, Nagwa M. El-Mak...
184
Voted
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 5 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
118
Voted
IJON
2002
103views more  IJON 2002»
15 years 3 months ago
RBF networks training using a dual extended Kalman filter
: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...
Iulian B. Ciocoiu
136
Voted
ICMLA
2009
15 years 1 months ago
Structured Prediction with Relative Margin
In structured prediction problems, outputs are not confined to binary labels; they are often complex objects such as sequences, trees, or alignments. Support Vector Machine (SVM) ...
Pannagadatta K. Shivaswamy, Tony Jebara