Results 21 to 30 of about 102,167 (290)
Relational Regularization and Feature Ranking [PDF]
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014 Regularization is one of the key concepts in machine learning, but so far it has received only little attention in the logical and relational learning setting. Here we propose a regularization and feature selection technique for such setting, in which one commonly represents the structure of the domain using an entity-relationship model.
Fabrizio Costa +2 more
openaire +2 more sources
Information, 2022 Globally, smart cities, infrastructure, and transportation have led to a rise in vehicle numbers, resulting in an increasing number of problems. This includes problems such as air pollution, noise pollution, high energy consumption, and people’s health ...
Manish Kumar Pandey +4 more
doaj +1 more source
Feature-ranking of the Iris dataset, according to our proposed optimally-separating ANN.
, 2021 Feature-ranking of the Iris dataset, according to our proposed optimally-separating ANN.
Yiting Tsai (4614913) +2 more
core +1 more source
Frontiers in Veterinary Science, 2023 IntroductionMyxomatous mitral valve disease (MMVD) is the most common cause of heart failure in dogs, and assessing the risk of heart failure in dogs with MMVD is often challenging.
Yunji Kim +5 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
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
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 +2 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
Wrapper for Ranking Feature Selection [PDF]
, 2004 We propose a new feature selection criterion not based on calculated measures between attributes, or complex and costly distance calculations. Applying a wrapper to the output of a new attribute ranking method, we obtain a minimum subset with the same error rate as the original data.
Roberto Ruiz +2 more
openaire +2 more sources
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