Performing feature selection with multilayer perceptrons
E Romero, JM Sopena - IEEE Transactions on Neural …, 2008 - ieeexplore.ieee.org
An experimental study on two decision issues for wrapper feature selection (FS) with
multilayer perceptrons and the sequential backward selection (SBS) procedure is presented …
multilayer perceptrons and the sequential backward selection (SBS) procedure is presented …
Improving the Mann–Whitney statistical test for feature selection: An approach in breast cancer diagnosis on mammography
Objective This work addresses the theoretical description and experimental evaluation of a
new feature selection method (named uFilter). The uFilter improves the Mann–Whitney U …
new feature selection method (named uFilter). The uFilter improves the Mann–Whitney U …
Improving the performance of machine learning classifiers for Breast Cancer diagnosis based on feature selection
This paper proposed a comprehensive algorithm for building machine learning classifiers for
Breast Cancer diagnosis based on the suitable combination of feature selection methods …
Breast Cancer diagnosis based on the suitable combination of feature selection methods …
Novel network architecture and learning algorithm for the classification of mass abnormalities in digitized mammograms
B Verma - Artificial Intelligence in Medicine, 2008 - Elsevier
OBJECTIVE: The main objective of this paper is to present a novel learning algorithm for the
classification of mass abnormalities in digitized mammograms. METHODS AND MATERIAL …
classification of mass abnormalities in digitized mammograms. METHODS AND MATERIAL …
Improving classification accuracy using combined filter+ wrapper feature selection technique
MSS Sumi, A Narayanan - 2019 IEEE International Conference …, 2019 - ieeexplore.ieee.org
Large datasets such as medical datasets contain a lot of redundant or irrelevant attributes
which will degrade the performance of the classifier. Feature selection methods help to …
which will degrade the performance of the classifier. Feature selection methods help to …
Detection of cancer tumors in mammography images using support vector machine and mixed gravitational search algorithm
In this paper, support vector machine (SVM) and mixed gravitational search algorithm
(MGSA) are utilized to detect the breast cancer tumors in mammography images. Sech …
(MGSA) are utilized to detect the breast cancer tumors in mammography images. Sech …
Neural–genetic synthesis for state-space controllers based on linear quadratic regulator design for eigenstructure assignment
JV da Fonseca Neto, IS Abreu… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
Toward the synthesis of state-space controllers, a neural–genetic model based on the linear
quadratic regulator design for the eigenstructure assignment of multivariable dynamic …
quadratic regulator design for the eigenstructure assignment of multivariable dynamic …
Classification of breast tissue in mammograms using efficient coding
DD Costa, LF Campos, AK Barros - Biomedical Engineering Online, 2011 - Springer
Background Female breast cancer is the major cause of death by cancer in western
countries. Efforts in Computer Vision have been made in order to improve the diagnostic …
countries. Efforts in Computer Vision have been made in order to improve the diagnostic …
A new hybrid method combining genetic algorithm and support vector machine classifier: Application to CAD system for mammogram images
Breast cancer continues to be one of the most common cancers, and survival rates critically
depend on its detection in the initial stages. Several studies have demonstrated the benefits …
depend on its detection in the initial stages. Several studies have demonstrated the benefits …
Bacteria foraging based independent component analysis
The present paper proposes a bacteria foraging optimization based independent
component analysis (BFOICA) algorithm assuming a linear noise free model. It is observed …
component analysis (BFOICA) algorithm assuming a linear noise free model. It is observed …