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» Privacy-preserving logistic regression
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ICPR
2008
IEEE
14 years 27 days ago
Locality preserving multi-nominal logistic regression
In this paper, we propose a novel algorithm of multi-nominal logistic regression in which the locality regularization term is introduced. The locality is defined by the neighborho...
Kenji Watanabe, Takio Kurita
NAACL
2010
13 years 4 months ago
Painless Unsupervised Learning with Features
We show how features can easily be added to standard generative models for unsupervised learning, without requiring complex new training methods. In particular, each component mul...
Taylor Berg-Kirkpatrick, Alexandre Bouchard-C&ocir...
AAAI
2006
13 years 7 months ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
ECRIME
2007
13 years 10 months ago
A comparison of machine learning techniques for phishing detection
There are many applications available for phishing detection. However, unlike predicting spam, there are only few studies that compare machine learning techniques in predicting ph...
Saeed Abu-Nimeh, Dario Nappa, Xinlei Wang, Suku Na...
CSDA
2007
137views more  CSDA 2007»
13 years 6 months ago
Fitting finite mixtures of generalized linear regressions in R
R package flexmix provides flexible modelling of finite mixtures of regression models using the EM algorithm. Several new features of the software such as fixed and nested var...
Bettina Grün, Friedrich Leisch