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Reproducible research by design: design principles for low-code/no-code AutoML tools [PDF]
Frontiers in Research Metrics and AnalyticsReproducibility is a major challenge for responsible machine learning (ML) research, especially with low-code/no-code automated ML (LCNC AutoML) tools making ML methods accessible to researchers outside data science.
Armin Haberl, Stefan Thalmann
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AI, 2023 Globally, over 17 million people annually die from cardiovascular diseases, with heart disease being the leading cause of mortality in the United States.
Tahir Cetin Akinci, Oguzhan Topsakal
exaly +3 more sources
Evaluating a New Auto-ML Approach for Sentiment Analysis and Intent Recognition Tasks
Journal on Interactive Systems, 2023 Automated Machine Learning (AutoML) is a research area that aims to help humans solve Machine Learning (ML) problems by automatically discovering good ML pipelines (algorithms and their hyperparameters for every stage of a machine learning process) for ...
Douglas Nunes de Oliveira +6 more
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Automated Machine Learning for Healthcare and Clinical Notes Analysis
Computers, 2021 Machine learning (ML) has been slowly entering every aspect of our lives and its positive impact has been astonishing. To accelerate embedding ML in more applications and incorporating it in real-world scenarios, automated machine learning (AutoML) is ...
Akram Mustafa, Mostafa Rahimi Azghadi
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Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial
Journal of Medical Internet Research, 2023 Deep learning–based clinical imaging analysis underlies diagnostic artificial intelligence (AI) models, which can match or even exceed the performance of clinical experts, having the potential to revolutionize clinical practice. A wide variety
Arun James Thirunavukarasu +7 more
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DETECTION OF SOURCE CODE IN INTERNET TEXTS USING AUTOMATICALLY GENERATED MACHINE LEARNING MODELS [PDF]
Applied Computer Science, 2022 In the paper, the authors are presenting the outcome of web scraping software allowing for the automated classification of source code. The software system was prepared for a discussion forum for software developers to find fragments of source code ...
Marcin BADUROWICZ
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Human behavior in image-based Road Health Inspection Systems despite the emerging AutoML
Journal of Big Data, 2022 Introduction The emergence of automated machine learning or AutoML has raised an interesting trend of no-code and low-code machine learning where most tasks in the machine learning pipeline can possibly be automated without support from human data ...
Thitirat Siriborvornratanakul
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A meta-feature selection method based on the Auto-sklearn framework [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2021 In recent years, the task of selecting and tuning machine learning algorithms has been increasingly solved using automated frameworks. This is motivated by the fact that when dealing with large amounts of data, classical methods are not efficient in ...
Nikita I. Kulin, Sergey B. Muravyov
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Classification Research on Emotion in Speech of Grid Customers Based on AutoML
Zhejiang dianli, 2022 The recognition of emotion in speech of customers is of great significance to grid operation. However， the recognition model of emotion in speech is designed by experts， which imposes restrictions on the application of artificial intelligence. This paper
SHEN Ran +3 more
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Using Machine Learning in Forestry
Turkish Journal of Forestry, 2023 Advanced technology has increased demands and needs for innovative approaches to apply traditional methods more economically, effectively, fast and easily in forestry, as in other disciplines.
Kamber Can Alkiş +3 more
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