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» Support vector machine via nonlinear rescaling method
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HCI
2009
13 years 5 months ago
Ensemble SWLDA Classifiers for the P300 Speller
Abstract. The P300 Speller has proven to be an effective paradigm for braincomputer interface (BCI) communication. Using this paradigm, studies have shown that a simple linear clas...
Garett D. Johnson, Dean J. Krusienski
TKDE
2010
182views more  TKDE 2010»
13 years 5 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 7 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
SMC
2007
IEEE
133views Control Systems» more  SMC 2007»
14 years 1 months ago
Text classification using multi-word features
—We carried out a series of experiments on text classification using multi-word features. An automated method was proposed to extract the multi-words from text data set and two d...
Wen Zhang, Taketoshi Yoshida, Xijin Tang
NIPS
2000
13 years 8 months ago
The Kernel Trick for Distances
A method is described which, like the kernel trick in support vector machines (SVMs), lets us generalize distance-based algorithms to operate in feature spaces, usually nonlinearl...
Bernhard Schölkopf