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» Markov Blanket Feature Selection for Support Vector Machines
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JMLR
2012
11 years 10 months ago
Maximum Margin Temporal Clustering
Temporal Clustering (TC) refers to the factorization of multiple time series into a set of non-overlapping segments that belong to k temporal clusters. Existing methods based on e...
Minh Hoai Nguyen, Fernando De la Torre
PAMI
2010
192views more  PAMI 2010»
13 years 6 months ago
Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...
Carlos Alzate, Johan A. K. Suykens
FSKD
2007
Springer
98views Fuzzy Logic» more  FSKD 2007»
14 years 1 months ago
Learning Selective Averaged One-Dependence Estimators for Probability Estimation
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
Qing Wang, Chuan-hua Zhou, Jiankui Guo
BMCBI
2006
110views more  BMCBI 2006»
13 years 7 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
JCP
2008
167views more  JCP 2008»
13 years 7 months ago
Accelerated Kernel CCA plus SVDD: A Three-stage Process for Improving Face Recognition
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Ming Li, Yuanhong Hao