Results 21 to 30 of about 461,060 (258)
Learning Feature Engineering for Classification [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Feature engineering is the task of improving predictive modelling performance on a dataset by transforming its feature space. Existing approaches to automate this process rely on either transformed feature space exploration through evaluation-guided search, or explicit expansion of datasets with all transformed features followed by feature selection ...
Fatemeh Nargesian +4 more
openaire +1 more source
Flavor changes of Yunnan large-leaf cultivar white tea during different aging periods
Food Chemistry: XYunnan large-leaf white tea gains popularity for its unique flavor attributable to the local tea varieties and environments. But how aging crucially enhances its quality and flavor remains unclear. Here, flavor change and safety quality of “Qinghuan” (QH)
Caibi Zhou +6 more
doaj +1 more source
Jurnal Teknologi Informasi dan Ilmu KomputerRisiko kredit adalah hal yang penting untuk dianalisis di awal pengajuan kredit guna mengurangi nilai Non-Performing Loan (NPL) atau risiko gagal bayar.
Nadea Putri Nur Fauzi +2 more
doaj +3 more sources
An End-to-End Rumor Detection Model Based on Feature Aggregation
Complexity, 2021 The social network has become the primary medium of rumor propagation. Moreover, manual identification of rumors is extremely time-consuming and laborious. It is crucial to identify rumors automatically.
Aoshuang Ye +5 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Leukemia is the most common childhood cancer in Mexico, and acute lymphoblastic leukemia (ALL) is the most frequent subtype. Exposure to high concentrations of benzene has been associated with ALL incidence, particularly in urban areas. This study evaluated the relationship between distance to benzene emission sources and the number
Orlando Rivera Zurita +5 more
wiley +1 more source
Feature engineering through two-level genetic algorithm
Machine Learning with ApplicationsDeep learning models are widely used for their high predictive performance, but often lack interpretability. Traditional machine learning methods, such as logistic regression and ensemble models, offer greater interpretability but typically have lower ...
Aditi Gulati +2 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Medication nonadherence during the first 100 days after pediatric hematopoietic stem cell transplantation (HSCT) and during oncology treatment increases risk for complications. BMT4me is a caregiver‐facing mobile health (mHealth) application providing medication reminders, symptom tracking, and note‐taking features to support ...
Micah A. Skeens +4 more
wiley +1 more source
Improving materials property predictions for graph neural networks with minimal feature engineering
Machine Learning: Science and Technology, 2023 Graph neural networks (GNNs) have been employed in materials research to predict physical and functional properties, and have achieved superior performance in several application domains over prior machine learning approaches.
Guojing Cong, Victor Fung
doaj +1 more source
Automation of feature engineering for IoT analytics [PDF]
ACM SIGBED Review, 2018 This paper presents an approach for automation of interpretable feature selection for Internet Of Things Analytics (IoTA) using machine learning (ML) techniques. Authors have conducted a survey over different people involved in different IoTA based application development tasks.
Snehasis Banerjee +3 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Anthracycline‐related cardiac remodeling precedes heart failure in childhood cancer survivors. The objectives of this study were to determine the relationships between patient‐specific factors, moderate‐to‐vigorous physical activity (MVPA), and cardiac remodeling.
Hari K. Narayan +15 more
wiley +1 more source