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ICDE
2000
IEEE
130views Database» more  ICDE 2000»
15 years 15 days ago
CMP: A Fast Decision Tree Classifier Using Multivariate Predictions
Most decision tree classifiers are designed to keep class histograms for single attributes, and to select a particular attribute for the next split using said histograms. In this ...
Haixun Wang, Carlo Zaniolo
SAC
2005
ACM
14 years 4 months ago
Learning decision trees from dynamic data streams
: This paper presents a system for induction of forest of functional trees from data streams able to detect concept drift. The Ultra Fast Forest of Trees (UFFT) is an incremental a...
João Gama, Pedro Medas, Pedro Pereira Rodri...
TCSV
2008
139views more  TCSV 2008»
13 years 11 months ago
A Fast MB Mode Decision Algorithm for MPEG-2 to H.264 P-Frame Transcoding
Abstract--The H.264 standard achieves much higher coding efficiency than the MPEG-2 standard, due to its improved inter-and intra-prediction modes at the expense of higher computat...
Gerardo Fernández-Escribano, Hari Kalva, Pe...
CEAS
2007
Springer
14 years 3 months ago
Learning Fast Classifiers for Image Spam
Recently, spammers have proliferated "image spam", emails which contain the text of the spam message in a human readable image instead of the message body, making detect...
Mark Dredze, Reuven Gevaryahu, Ari Elias-Bachrach
ESANN
2006
14 years 17 days ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...