Decision making methods based on fuzzy aggregation operators: Three decades review from 1986 to 2017
In many real-life decision making (DM) situations, the available information is vague or
imprecise. To adequately solve decision problems with vague or imprecise information …
imprecise. To adequately solve decision problems with vague or imprecise information …
Particle swarm optimization feature selection for breast cancer recurrence prediction
Women who have recovered from breast cancer (BC) always fear its recurrence. The fact
that they have endured the painstaking treatment makes recurrence their greatest fear …
that they have endured the painstaking treatment makes recurrence their greatest fear …
Modified binary PSO for feature selection using SVM applied to mortality prediction of septic patients
SM Vieira, LF Mendonça, GJ Farinha… - Applied Soft Computing, 2013 - Elsevier
This paper proposes a modified binary particle swarm optimization (MBPSO) method for
feature selection with the simultaneous optimization of SVM kernel parameter setting …
feature selection with the simultaneous optimization of SVM kernel parameter setting …
A novel enhanced hybrid clinical decision support system for accurate breast cancer prediction
Feature selection is one of the crucial data preprocessing techniques for improving the
performance of machine learning (ML) models. Recently, metaheuristic feature selection …
performance of machine learning (ML) models. Recently, metaheuristic feature selection …
Automated machine learning with interpretation: a systematic review of methodologies and applications in healthcare
Abstract Machine learning (ML) has achieved substantial success in performing healthcare
tasks in which the configuration of every part of the ML pipeline relies heavily on technical …
tasks in which the configuration of every part of the ML pipeline relies heavily on technical …
Driver drowsiness detection based on steering wheel data applying adaptive neuro-fuzzy feature selection
This paper presents a novel feature selection method to design a non-invasive driver
drowsiness detection system based on steering wheel data. The proposed feature selector …
drowsiness detection system based on steering wheel data. The proposed feature selector …
Feature subset selection filter–wrapper based on low quality data
Today, feature selection is an active research in machine learning. The main idea of feature
selection is to choose a subset of available features, by eliminating features with little or no …
selection is to choose a subset of available features, by eliminating features with little or no …
Reducing unnecessary lab testing in the ICU with artificial intelligence
OBJECTIVES: To reduce unnecessary lab testing by predicting when a proposed future lab
test is likely to contribute information gain and thereby influence clinical management in …
test is likely to contribute information gain and thereby influence clinical management in …
Feature selection using multimodal optimization techniques
This paper investigates the effect of using Multimodal Optimization (MO) techniques on
solving the Feature Selection (FSel) problem. The FSel problem is a high-dimensional …
solving the Feature Selection (FSel) problem. The FSel problem is a high-dimensional …
Global geometric similarity scheme for feature selection in fault diagnosis
C Liu, D Jiang, W Yang - Expert Systems with Applications, 2014 - Elsevier
This work presents a global geometric similarity scheme (GGSS) for feature selection in fault
diagnosis, which is composed of global geometric model and similarity metric. The global …
diagnosis, which is composed of global geometric model and similarity metric. The global …