Results 61 to 70 of about 6,098 (213)
Safety Science and Technology, EarlyView.A LightGBM‐based ensemble learning framework with SHAP interpretability analysis was developed for predicting ceiling temperature in canyon‐wind tunnel fires. The model demonstrated robust generalization (R2 = 0.7476) under unseen extreme conditions, with fire‐source location identified as the primary factor driving temperature evolution.
Qinqin Zhu +5 more
wiley +1 more source
Residual permutation tests for feature importance in machine learning
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Psychological research has traditionally relied on linear models to test scientific hypotheses. However, the emergence of machine learning (ML) algorithms has opened new opportunities for exploring variable relationships beyond linear constraints.
Po‐Hsien Huang
wiley +1 more source
The autoML jungle - An overview
, 2021 Hardly any other research area has attracted as much attention as machine learning. It is a challenging task to build well performing machine learning applications and therefore requires highly specialized data scientists.
Kirikkayis, Yusuf
core +1 more source
Sulaimani Journal for Engineering SciencesThe vast expansion of IoT devices significantly expands the potential attack surface for networks; therefore, the increased complexity in detecting intrusions from these new sources is caused by the large dimensionality of the data, the severe class ...
Susan M. Al Naqshbandi
doaj +1 more source
Scientific Reports, 2022 To investigate the applicability and performance of automated machine learning (AutoML) for potential applications in diagnostic neuroradiology. In the medical sector, there is a rapidly growing demand for machine learning methods, but only a limited ...
Manfred Musigmann +10 more
doaj +1 more source
A hybrid strategy of AutoML and SHAP for automated and explainable concrete strength prediction
Case Studies in Construction Materials, 2023 The precise prediction of concrete compressive strength is essential for ensuring safe and reliable infrastructure design and construction. However, traditional empirical models often struggle to accurately predict compressive strength due to the complex
Bochao Sun +4 more
doaj +1 more source
Autotext: autoML for text classification [PDF]
, 2019 Non-experts in Machine Learning research have an increasing demand for easy-to-use methods to model solutions that use the large amounts of data available today, where such solutions are expected to perform at least as well as one build by a human with ...
Jorge Madrid
core
Improving Automated Machine-Learning Systems through Green AI
Applied Sciences, 2023 Automated machine learning (AutoML), which aims to facilitate the design and optimization of machine-learning models with reduced human effort and expertise, is a research field with significant potential to drive the development of artificial ...
Dagoberto Castellanos-Nieves +1 more
doaj +1 more source
Periodontology 2000, EarlyView.Abstract Background Artificial intelligence (AI) is increasingly gaining attention in the field of periodontology and implant dentistry. Currently developed models can support diagnosis, treatment planning, and maintenance monitoring. However, most of the available literature is based on retrospective and often single‐modality data sets.
Aminollah Khormali +2 more
wiley +1 more source
Smart Agricultural TechnologyAutomated machine learning (AutoML) is considered the next advancement in artificial intelligence due to its commitment to delivering high-performance end-to-end machine learning pipelines with minimal user input.
Ioannis Malounas +3 more
doaj +1 more source