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ICMCS
2006
IEEE
105views Multimedia» more  ICMCS 2006»
14 years 2 months ago
Entropy and Memory Constrained Vector Quantization with Separability Based Feature Selection
An iterative model selection algorithm is proposed. The algorithm seeks relevant features and an optimal number of codewords (or codebook size) as part of the optimization. We use...
Sangho Yoon, Robert M. Gray
ICTAI
1993
IEEE
14 years 29 days ago
Robust Feature Selection Algorithms
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive cont...
Haleh Vafaie, Kenneth DeJong
ICPR
2006
IEEE
14 years 10 months ago
Feature selection based on the training set manipulation
A novel filter feature selection technique is introduced. The method exploits the information conveyed by the evolution of the training samples weights similarly to the Adaboost a...
Pavel Krízek, Josef Kittler, Václav ...
SPLC
2010
13 years 7 months ago
Stratified Analytic Hierarchy Process: Prioritization and Selection of Software Features
Product line engineering allows for the rapid development of variants of a domain specific application by using a common set of reusable assets often known as core assets. Variabil...
Ebrahim Bagheri, Mohsen Asadi, Dragan Gasevic, Sam...
JIPS
2006
72views more  JIPS 2006»
13 years 8 months ago
A Feature Selection Technique based on Distributional Differences
: This paper presents a feature selection technique based on distributional differences for efficient machine learning. Initial training data consists of data including many featur...
Sung-Dong Kim