Results 51 to 60 of about 1,793,798 (289)
Multivariate feature ranking of gene expression data [PDF]
, 2022 Gene expression datasets are usually of high dimensionality and therefore require efficient and effective methods for identifying the relative importance of their attributes.
Sánchez, Gracia +4 more
core +1 more source
Supervised Feature Selection With a Stratified Feature Weighting Method
IEEE Access, 2018 Feature selection has been a powerful tool to handle high-dimensional data. Most of these methods are biased toward the highest rank features which may be highly correlated with each other.
Renjie Chen +4 more
doaj +1 more source
Neural Feature Selection for Learning to Rank [PDF]
, 2021 AbstractLEarning TO Rank (LETOR) is a research area in the field of Information Retrieval (IR) where machine learning models are employed to rank a set of items. In the past few years, neural LETOR approaches have become a competitive alternative to traditional ones like LambdaMART. However, neural architectures performance grew proportionally to their
Purpura A. +3 more
openaire +3 more sources
Central Nervous System Tumors Among Infants in Canada: A Report From CYP‐C
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Central nervous system (CNS) tumors in infants are rare, pose unique clinical challenges, and lack large‐scale evidence‐based data to guide management. This study seeks to describe CNS tumors in Canadian infants and to compare their outcomes with those of older children.
Samuel Sassine +17 more
wiley +1 more source
IEEE AccessBruxism is a sleep disorder which is manifested by unintentional grinding and clenching of teeth during sleep. An automated sleep bruxism recognition system using single channel EEG data is proposed in this paper which is based on Inverse Discrete ...
Ainul Anam Shahjamal Khan +3 more
doaj +1 more source
Feature ranking in hoeffding algorithms for regression [PDF]
Proceedings of the Symposium on Applied Computing, 2017 Feature selection and feature ranking are two aspects of the same learning task. They are well studied in batch scenarios, but not in the streaming setting. This paper presents a study on feature ranking from data streams in online learning regression models. The main challenge here is the relevance of features might change over time: features relevant
João Duarte, João Gama 0001
openaire +2 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Introduction This study investigated the safety and efficacy of single‐needle Rheocarna therapy for chronic limb‐threatening ischemia (CLTI) with wounds. Methods Six patients with CLTI involving ulcers unresponsive to revascularization underwent single‐needle Rheocarna treatment.
Yasutaka Yamauchi +9 more
wiley +1 more source
Feature importance ranking from RF.
, 2022 Feature importance ranking from RF.
Yuge Li (13511948) +6 more
core +1 more source
Machine Learning for Extraction of Image Features Associated with Progression of Geographic Atrophy
BioMedInformaticsBackground: Several studies have investigated various features and models in order to understand the growth and progression of the ocular disease geographic atrophy (GA).
Janan Arslan, Kurt Benke
doaj +1 more source
An Improved Ranking-Based Feature Enhancement Approach for Robust Speaker Recognition
IEEE Access, 2016 Although the field of automatic speaker or speech recognition has been extensively studied over the past decades, the lack of robustness has remained a major challenge.
Furong Yan +3 more
doaj +1 more source