Results 41 to 50 of about 1,151,147 (311)

Hybrid Machine Learning-Based Multi-Stage Framework for Detection of Credit Card Anomalies and Fraud

IEEE Access
Recently, tremendous growth in e-business has arisen in an increasing number of online transactions. Such widespread adaptation of e-payments has been going along with the increase in deceitful activities, which results in tremendous losses in the ...
Hatoon S. Alsagri
doaj   +1 more source

Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms

Entropy, 2013
Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance.
Fernando A. Auat Cheein
doaj   +1 more source

Text summarization features selection method using pseudo genetic-based model [PDF]

, 2012
The features are considered the cornerstone of text summarization. The most important issue is what feature to be considered in a text summarization process.
Kumar, Y. J., Albaham, A. T., Abuobieda, A., Osman, A. H., Salim, Naomie   +4 more
core   +1 more source

Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield and Amygdala Volume of Structural MRI

Frontiers in Aging Neuroscience, 2022
Accurate diagnosis of the initial phase of Alzheimer’s disease (AD) is essential and crucial. The objective of this research was to employ efficient biomarkers for the diagnostic analysis and classification of AD based on combining structural MRI (sMRI ...
Uttam Khatri, Goo-Rak Kwon
doaj   +1 more source

Features selection for offline handwritten signature verification: State of the art [PDF]

, 2018
This research comes out with an in-depth review of widely used techniques to handwritten signature verification based, feature selection techniques. The focus of this research is to explore best features selection criteria for signature verification to ...
Ebrahim, Anwar Yahya, Kolivand, H, Kolivand, Hoshang, Rehman, Amjad, Mohd. Rahim, Mohd. Shafry, Saba, Tanzila, Ebrahim, AY, Rehman, A, Rahim, MSM, Saba, T   +9 more
core   +1 more source

European Standard Clinical Practice Guideline and EXPeRT Recommendations for the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms in Children and Adolescents

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen, Calogero Virgone, Antje Redlich, Michael Abele, Ricardo Lopez‐Almaraz, Tal Ben‐Ami, Ewa Bien, Gianni Bisogno, Maja Mazic Cesen, Andrea Ferrari, Malgorzata A. Krawczyk, Yves Reguerre, Dominik T. Schneider, Ines B. Brecht, Charlotte Rigaud, Bilgehan Yalcin, Rainer Claus, Christian Vokuhl, Constantin Lapa, Jörg Fuchs, Segolene Hescot, Thomas Walter, Julien Hadoux, Daniel Orbach   +23 more
wiley   +1 more source

Improved Feature Selection and Stream Traffic Classification Based on Machine Learning in Software-Defined Networks

IEEE Access
Traffic classification (TC) in software-defined networks (SDN) using machine learning (ML) appears to be a viable option for improving network management.
Arwa M. Eldhai, Mosab Hamdan, Ahmed Abdelaziz, Ibrahim Abaker Targio Hashem, Sharief F. Babiker, M. N. Marsono, Muzaffar Hamzah, Noor Zaman Jhanjhi   +7 more
doaj   +1 more source

Ensemble Deep Learning Models for Heart Disease Classification: A Case Study from Mexico

Information, 2020
Heart diseases are highly ranked among the leading causes of mortality in the world. They have various types including vascular, ischemic, and hypertensive heart disease.
Asma Baccouche, Begonya Garcia-Zapirain, Cristian Castillo Olea, Adel Elmaghraby   +3 more
doaj   +1 more source

Population Initialization Factor in Binary Multi-Objective Grey Wolf Optimization for Features Selection

IEEE Access, 2022
Features selection methods not only reduce the dimensionality, but also improve significantly the classification results. In this study, the effect of the initialization population using the population factor has been explored.
Nur Lyana Shahfiqa Albashah, Helmi Md Rais   +1 more
doaj   +1 more source

Feature Selection Ensemble

EPiC Series in Computing, 2018
Many strategies have been exploited for the task of feature selection, in an effort to identify more compact and better quality feature subsets. Such techniques typically involve the use of an individual feature significance evaluation, or a measurement of feature subset consistency, that work together with a search algorithm in order to determine a ...
Qiang Shen 0001, Ren Diao, Pan Su 0001
openaire   +2 more sources