Results 21 to 30 of about 2,058,652 (297)
Feature importance ranking from RF.
, 2022 Feature importance ranking from RF.
Yuge Li (13511948) +6 more
core +1 more source
Ensemble feature selection approach based on feature ranking for rice seed images classification
Advances in Electrical and Electronic Engineering, 2020 In smart agriculture, rice variety inspection systems based on computer vision need to be used for recognizing rice seeds instead of using technical experts.
Dzi Lam Tran Tuan +3 more
doaj +1 more source
Deep Feature Ranking for Person Re-Identification
IEEE Access, 2019 Person re-identification plays a critical part in many surveillance applications. Due to complicated illumination environments and various viewpoints, it is still a challenging problem to extract robust features.
Jie Nie +4 more
doaj +1 more source
Feature ranking for semi-supervised learning
Machine Learning, 2022 AbstractThe data used for analysis are becoming increasingly complex along several directions: high dimensionality, number of examples and availability of labels for the examples. This poses a variety of challenges for the existing machine learning methods, related to analyzing datasets with a large number of examples that are described in a high ...
Matej Petkovic +2 more
openaire +3 more sources
Alternative Relative Discrimination Criterion Feature Ranking Technique for Text Classification
IEEE Access, 2023 The use of text data with high dimensionality affects classifier performance. Therefore, efficient feature selection (FS) is necessary to reduce dimensionality.
Sarah Abdulkarem Alshalif +6 more
doaj +1 more source
Feature ranking for the Full Oklahoma dataset.
, 2022 Feature ranking for the Full Oklahoma dataset.
Rachel Bennett (7649594) +4 more
core +1 more source
Feature name and associated ranking.
, 2020 Feature name and associated ranking.
Md. Raihan-Al-Masud (8415444) +1 more
core +1 more source
Decision Support System for Predicting Mortality in Cardiac Patients Based on Machine Learning
Applied Sciences, 2023 Researchers have proposed several automated diagnostic systems based on machine learning and data mining techniques to predict heart failure. However, researchers have not paid close attention to predicting cardiac patient mortality.
Ashir Javeed +5 more
doaj +1 more source
Feature factors importance ranking of RF model.
, 2022 Feature factors importance ranking of RF model.
Kaixiang Zhang (1592236) +2 more
core +1 more source
Number of Instances for Reliable Feature Ranking in a Given Problem
Business Systems Research, 2018 Background: In practical use of machine learning models, users may add new features to an existing classification model, reflecting their (changed) empirical understanding of a field. New features potentially increase classification accuracy of the model
Bohanec Marko +2 more
doaj +1 more source