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105
Voted
ICML
1994
IEEE
15 years 4 months ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak
110
Voted
CBMS
2008
IEEE
15 years 3 months ago
Effectiveness of Local Feature Selection in Ensemble Learning for Prediction of Antimicrobial Resistance
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may ...
Seppo Puuronen, Mykola Pechenizkiy, Alexey Tsymbal
BMCBI
2004
181views more  BMCBI 2004»
15 years 1 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
129
Voted
ENC
2004
IEEE
15 years 4 months ago
Feature Selection for Visual Gesture Recognition Using Hidden Markov Models
Hidden Markov models have become the preferred technique for visual recognition of human gestures. However, the recognition rate depends on the set of visual features used, and al...
José Antonio Montero, Luis Enrique Sucar
103
Voted
IEAAIE
2003
Springer
15 years 6 months ago
Fast Feature Selection by Means of Projections
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simple...
Roberto Ruiz, José Cristóbal Riquelm...