Results 31 to 40 of about 96,228 (258)

Neighborhood Ranking-Based Feature Selection

IEEE Access
This article aims to integrate ${k}$ -NN regression, false-nearest neighborhood (FNN), and trustworthiness and continuity (T&C) neighborhood-based measures into an efficient and robust feature selection method to support the identification of ...
Adam Ipkovich, Janos Abonyi
doaj   +1 more source

Predicting Diabetes Mellitus With Machine Learning Techniques

Frontiers in Genetics, 2018
Diabetes mellitus is a chronic disease characterized by hyperglycemia. It may cause many complications. According to the growing morbidity in recent years, in 2040, the world’s diabetic patients will reach 642 million, which means that one of the ten ...
Quan Zou, Quan Zou, Kaiyang Qu, Yamei Luo, Dehui Yin, Ying Ju, Hua Tang   +6 more
doaj   +1 more source

Application of Biological Domain Knowledge Based Feature Selection on Gene Expression Data

Entropy, 2020
In the last two decades, there have been massive advancements in high throughput technologies, which resulted in the exponential growth of public repositories of gene expression datasets for various phenotypes.
Malik Yousef, Abhishek Kumar, Burcu Bakir-Gungor   +2 more
doaj   +1 more source

Identification of Critical Components in the Complex Technical Infrastructure of the Large Hadron Collider Using Relief Feature Ranking and Support Vector Machines

Energies, 2021
This work proposes a data-driven methodology for identifying critical components in Complex Technical Infrastructures (CTIs), for which the functional logic and/or the system structure functions are not known due the CTI’s complexity and evolving nature.
Ahmed Shokry, Piero Baraldi, Andrea Castellano, Luigi Serio, Enrico Zio   +4 more
doaj   +1 more source

Learning to Rank 3D Features [PDF]

, 2014
Representation of three dimensional objects using a set of oriented point pair features has been shown to be effective for object recognition and pose estimation. Combined with an efficient voting scheme on a generalized Hough space, existing approaches achieve good recognition accuracy and fast operation.
Oncel Tuzel, Ming-Yu Liu 0001, Yuichi Taguchi, Arvind Raghunathan   +3 more
openaire   +1 more source

Efficient Feature Ranking and Selection Using Statistical Moments

IEEE Access
Unsupervised feature selection methods can be more efficient than supervised methods, which rely on the expensive and time-consuming data labeling process.
Yael Hochma, Yuval Felendler, Mark Last
doaj   +1 more source

Feature-enriched author ranking in incomplete networks

Applied Network Science, 2019
Evaluating scientists based on their scientific production is a controversial topic. Nevertheless, bibliometrics and algorithmic approaches can assist traditional peer review in numerous tasks, such as attributing research grants, deciding scientific ...
Jorge Silva, David Aparício, Fernando Silva   +2 more
doaj   +1 more source

Measurable Residual Disease Monitoring During Treatment for Pediatric Acute Myeloid Leukemia in First Relapse

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Survival after relapse in pediatric acute myeloid leukemia (AML) remains poor, highlighting the critical importance of identifying prognostic factors to guide optimal relapse management. Methods We investigated the prognostic impact of multiparameter flow cytometry (MFC) measurable residual disease (MRD) in 188 patients with first ...
Camilla Poulsen, Kristian Juul Sandahl, Lene Karlsson, Jonas Abrahamsson, Nira Arad‐Cohen, Daniel Cheuk, Barbara De Moerloose, Linda Fogelstrand, Jose Maria Fernandez Navarro, Bianca F. Goemans, Kirsi Jahnukainen, Gertjan Kaspers, Zhanna Kovalova, Monica Cheng Munthe‐Kaas, Ulrika Norén‐Nyström, Josefine Palle, Ramune Pasauliene, Cornelis Jan Pronk, Kadri Saks, Anne Tierens, Henrik Hasle, Kristian Løvvik Juul‐Dam   +21 more
wiley   +1 more source

A novel somatic cancer gene-based biomedical document feature ranking and clustering model

Informatics in Medicine Unlocked, 2019
Background: As the size of somatic genomes in biomedical repositories increases, it is essential to predict cancer related document sets using the machine learning models. Most of the traditional gene-based somatic cancer mining models are independent of
Thulasi Bikku, Radhika Paturi
doaj   +1 more source

Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques

Mathematics, 2023
In this paper, we propose and compare new methodologies for ranking the importance of variables in productive processes via an adaptation of OneClass Support Vector Machines.
Raul Moragues, Juan Aparicio, Miriam Esteve   +2 more
doaj   +1 more source