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1611 |
How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences
Jiang, Shijie. - Jena : Friedrich-Schiller-Universität Jena, 2024
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1612 |
How to treat mixed behavior segments in supervised machine learning of behavioural modes from inertial measurement data
Resheff, Yehezkel S.. - Konstanz : KOPS Universität Konstanz, 2024
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1613 |
How valid are trust survey measures? New insights from open-ended probing data and supervised machine learning
Landesvatter, Camille. - Mannheim : Universitätsbibliothek Mannheim, 2024
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1614 |
Hyperparameter optimization of two-branch neural networks in multi-target prediction
Iliadis, Dimitrios. - Ludwig-Maximilians-Universität München, 2024
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1615 |
Identification and prediction of association patterns between nutrient intake and anemia using machine learning techniques: results from a cross-sectional study with university female students from Palestine
Qasrawi, Radwan. - Hannover : Gottfried Wilhelm Leibniz Universität Hannover, 2024
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1616 |
Identification of a machine learning-based diagnostic model for axial spondyloarthritis in rheumatological routine care using a random forest approach
Redeker, Imke. - Bochum : Ruhr-Universität Bochum, 2024
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1617 |
Identifying CBT non-response among OCD outpatients: A machine-learning approach
Hilbert, Kevin. - Berlin : Humboldt-Universität zu Berlin, 2024
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1618 |
Implementing machine learning techniques for continuous emotion prediction from uniformly segmented voice recordings
Diemerling, Hannes. - Berlin : Humboldt-Universität zu Berlin, 2024
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1619 |
Improved carbide volume fraction estimation in as-cast HCCI alloys using machine learning techniques
Nayak, U. Pranav. - Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2024
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1620 |
Improving forecasts of precipitation extremes over northern and central Italy using machine learning
Grazzini, Federico. - Ludwig-Maximilians-Universität München, 2024
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