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» Decision trees do not generalize to new variations
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DIS
2006
Springer
14 years 9 days ago
Incremental Algorithm Driven by Error Margins
Incremental learning is an approach to deal with the classification task when datasets are too large or when new examples can arrive at any time. One possible approach uses concent...
Gonzalo Ramos-Jiménez, José del Camp...
TMC
2002
118views more  TMC 2002»
13 years 8 months ago
Code Placement and Replacement Strategies for Wideband CDMA OVSF Code Tree Management
The use of OVSF codes in WCDMA systems has offered opportunities to provide variable data rates to flexibly support applications with different bandwidth requirements. Two importan...
Yu-Chee Tseng, Chih-Min Chao
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 9 months ago
Systematic data selection to mine concept-drifting data streams
One major problem of existing methods to mine data streams is that it makes ad hoc choices to combine most recent data with some amount of old data to search the new hypothesis. T...
Wei Fan
GECCO
2005
Springer
189views Optimization» more  GECCO 2005»
14 years 2 months ago
Molecular programming: evolving genetic programs in a test tube
We present a molecular computing algorithm for evolving DNA-encoded genetic programs in a test tube. The use of synthetic DNA molecules combined with biochemical techniques for va...
Byoung-Tak Zhang, Ha-Young Jang
NIPS
2001
13 years 10 months ago
Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference
Estimating insurance premia from data is a difficult regression problem for several reasons: the large number of variables, many of which are discrete, and the very peculiar shape...
Nicolas Chapados, Yoshua Bengio, Pascal Vincent, J...