Results 101 to 110 of about 102,167 (290)
Top-$k$ Feature Importance Ranking
CoRRAccurate ranking of important features is a fundamental challenge in interpretable machine learning with critical applications in scientific discovery and decision-making. Unlike feature selection and feature importance, the specific problem of ranking important features has received considerably less attention.
Eric Chen +2 more
openaire +3 more sources
Molecular Oncology, EarlyView.Intratumour heterogeneity complicates precision management of advanced endometrial cancer. Circulating tumor DNA (ctDNA) offers a minimally invasive strategy to capture tumor evolution and therapeutic resistance. Here, we compare tumor‐agnostic NGS with tumor‐informed ddPCR, outlining their relative sensitivity, concordance, and clinical implications ...
Carlos Casas‐Arozamena +15 more
wiley +1 more source
An Empirical Study on the Effectiveness of Feature Selection for Cross-Project Defect Prediction
IEEE Access, 2019 Software defect prediction has attracted much attention of researchers in software engineering. At present, feature selection approaches have been introduced into software defect prediction, which can improve the performance of traditional defect ...
Qiao Yu +4 more
doaj +1 more source
Molecular Oncology, EarlyView.Here, we demonstrate that HS1BP3 interacts with Cortactin through a proline‐rich region (PRR3.1) and show that this interaction, and HS1BP3 itself, promote cancer cell proliferation and invasion. Inhibition of this interaction leads to build‐up of TKS5 in multivesicular endosomes and altered secretion of CD63 and CD9, providing an explanation for the ...
Arja Arnesen Løchen +9 more
wiley +1 more source
An incremental approach to MSE-based feature selection
, 2007 Feature selection plays an important role in classification systems. Using classifier error rate as the evaluation function, feature selection is integrated with incremental training.
Guan, SU, Bao, C, Qi, Y
core
An Experimental Comparison of Feature-Selection and Classification Methods for Microarray Datasets
Information, 2019 In the last decade, there has been a growing scientific interest in the analysis of DNA microarray datasets, which have been widely used in basic and translational cancer research.
Nicole Dalia Cilia +4 more
doaj +1 more source
Iterative subtraction method for Feature Ranking
CoRR, 2019 Training features used to analyse physical processes are often highly correlated and determining which ones are most important for the classification is a non-trivial tasks. For the use case of a search for a top-quark pair produced in association with a Higgs boson decaying to bottom-quarks at the LHC, we compare feature ranking methods for a ...
Paul Glaysher +2 more
openaire +2 more sources
Interpreting the effects of DNA polymerase variants at the structural level
Molecular Oncology, EarlyView.Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi +7 more
wiley +1 more source
Intelligent feature based resource selection and process planning
, 2012 Lien vers la version éditeur: https://www.inderscience.com/books/index.php?action=record&rec_id=755&chapNum=3&journalID=1022&year=2010This paper presents an intelligent knowledge-based integrated manufacturing system using the STEP feature-based ...
MARTIN, Patrick +4 more
core
Training set feature ranking, by information gain.
, 2014 Training set feature ranking, by information gain.
Qing Zhang (1802), Hong Yu (6528)
core +1 more source