Filter feature selection based boolean modelling for genetic network inference
Abstract The reconstruction of Gene Regulatory Networks (GRNs) from time series gene
expression data is highly relevant for the discovery of complex biological interactions and …
expression data is highly relevant for the discovery of complex biological interactions and …
Transductive feature selection with maximum-relevancy and minimum-redundancy criteria
Various embodiments select features from a feature space. In one embodiment, a set of
training samples and a set of test samples are received. The set of training samples includes …
training samples and a set of test samples are received. The set of training samples includes …
Analysis of Electroencephalogram (EEG) Signals for Detection of Major Depressive Disorder (MDD) Using Feature Selection and Reduction Techniques
Extensive research has been done in identification of major depressive disorder (MDD) or
depression using various classifiers and features. Many features are extracted from each …
depression using various classifiers and features. Many features are extracted from each …
Feature selection for efficient epistasis modeling for phenotype prediction
Various embodiments select markers for modeling epistasis effects. In one embodiment, a
processor receives a set of genetic markers and a phenotype. A relevance score is …
processor receives a set of genetic markers and a phenotype. A relevance score is …
Transductive feature selection with maximum-relevancy and minimum-redundancy criteria
Various embodiments select features from a feature space. In one embodiment, a set of
training samples and a set of test samples are received. The set of training samples includes …
training samples and a set of test samples are received. The set of training samples includes …
Feature selection for efficient epistasis modeling for phenotype prediction
Various embodiments select markers for modeling epistasis effects. In one embodiment, a
processor receives a set of genetic markers and a phenotype. A relevance score is …
processor receives a set of genetic markers and a phenotype. A relevance score is …
Hill-climbing feature selection with max-relevancy and minimum redundancy criteria
Various embodiments select features from a feature space. In one embodiment a candidate
feature set of k′ features is selected from at least one set of features based on maximum …
feature set of k′ features is selected from at least one set of features based on maximum …
Feature selection for efficient epistasis modeling for phenotype prediction
Various embodiments select markers for modeling epistasis effects. In one embodiment, a
processor receives a set of genetic markers and a phenotype. A relevance score is …
processor receives a set of genetic markers and a phenotype. A relevance score is …
Feature selection for efficient epistasis modeling for phenotype prediction
Various embodiments select markers for modeling epistasis effects. In one embodiment, a
processor receives a set of genetic markers and a phenotype. A relevance score is …
processor receives a set of genetic markers and a phenotype. A relevance score is …
[图书][B] Spectral-spatial approaches for hyperspectral data classification
SR Roy - 2015 - search.proquest.com
Classification of hyperspectral data is very challenging and mapping of land cover is one of
its applications. Improving the classification accuracy and computation time of hyperspectral …
its applications. Improving the classification accuracy and computation time of hyperspectral …