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» Locally Weighted Naive Bayes
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ESANN
2007
13 years 9 months ago
Classifying n-back EEG data using entropy and mutual information features
In this work we show that entropy (H) and mutual information (MI) can be used as methods for extracting spatially localized features for classification purposes. In order to incre...
Liang Wu, Predrag Neskovic, Etienne Reyes, Elena F...
ICCV
2011
IEEE
12 years 7 months ago
The NBNN kernel
Naive Bayes Nearest Neighbor (NBNN) has recently been proposed as a powerful, non-parametric approach for object classification, that manages to achieve remarkably good results t...
Tinne Tuytelaars, Mario Fritz, Kate Saenko, Trevor...
ICML
1997
IEEE
14 years 8 months ago
A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization
The Rocchio relevance feedback algorithm is one of the most popular and widely applied learning methods from information retrieval. Here, a probabilistic analysis of this algorith...
Thorsten Joachims
ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
14 years 27 days ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof
BMCBI
2008
98views more  BMCBI 2008»
13 years 7 months ago
Empirical Bayes models for multiple probe type microarrays at the probe level
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
Magnus Åstrand, Petter Mostad, Mats Rudemo