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98
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IDA
2007
Springer
15 years 8 months ago
Combining Bagging and Random Subspaces to Create Better Ensembles
Random forests are one of the best performing methods for constructing ensembles. They derive their strength from two aspects: using random subsamples of the training data (as in b...
Pance Panov, Saso Dzeroski
125
Voted
CORR
2010
Springer
91views Education» more  CORR 2010»
14 years 8 months ago
TSDS: high-performance merge, subset, and filter software for time series-like data
Time Series Data Server (TSDS) is a software package for implementing a server that provides fast supersetting, sub-setting, filtering, and uniform gridding of time series-like dat...
Robert S. Weigel, Doug M. Lindholm, A. Wilson, Jer...
128
Voted
GECCO
2004
Springer
144views Optimization» more  GECCO 2004»
15 years 7 months ago
Feature Subset Selection, Class Separability, and Genetic Algorithms
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Erick Cantú-Paz
ICALP
1998
Springer
15 years 6 months ago
Efficient Approximation Algorithms for the Subset-Sums Equality Problem
We investigate the problem of finding two nonempty disjoint subsets of a set of n positive integers, with the objective that the sums of the numbers in the two subsets be as close ...
Cristina Bazgan, Miklos Santha, Zsolt Tuza
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
15 years 7 months ago
A genetic algorithm approach to the selection of near-optimal subsets from large sets
The problem attempted in this paper is to select a sample from a large set where the sample is required to have a particular average property. The problem can be expressed as an o...
P. Whiting, P. W. Poon, J. N. Carter