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26611 |
The Effect of Different Flaw Data to Machine Learning Powered Ultrasonic Inspection
Enthalten in Journal of nondestructive evaluation Bd. 40, 18.2.2021, Nr. 1, date:3.2021: 1-13
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26612 |
The effect of drought stress of sorghum grains on the textural features evaluated using machine learning
Enthalten in European food research and technology Bd. 247, 31.7.2021, Nr. 11, date:11.2021: 2787-2798
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26613 |
The effect of element characteristics on bainite transformation start temperature using a machine learning approach
Enthalten in Journal of materials science Bd. 58, 1.1.2023, Nr. 1, date:1.2023: 443-456
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26614 |
The effect of hazard shock and disclosure information on property and land prices: a machine-learning assessment in the case of Japan
Enthalten in Review of regional research Bd. 41, 24.1.2021, Nr. 1, date:2.2021: 1-32
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26615 |
The Effect of Informal Central Bank Communication: Machine Learning Approach
Enthalten in Atlantic economic journal Bd. 46, 1.6.2018, Nr. 2, date:6.2018: 241-242
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26616 |
The effect of machine learning tools for evidence synthesis on resource use and time-to-completion: protocol for a retrospective pilot study
Enthalten in Systematic Reviews Bd. 12, 17.1.2023, Nr. 1, date:12.2023: 1-8
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26617 |
The effect of resampling techniques on the performances of machine learning clinical risk prediction models in the setting of severe class imbalance: development and internal validation in a retrospective cohort
Enthalten in Discover artificial intelligence Bd. 4, 26.11.2024, Nr. 1, date:12.2024: 1-17
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26618 |
The effect of sport in online dating: evidence from causal machine learning
Enthalten in Humanities and Social Sciences Communications Bd. 12, 19.3.2025, Nr. 1, date:12.2025: 1-13
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26619 |
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear strength prediction
Enthalten in Stochastic environmental research and risk assessment Bd. 38, 13.6.2024, Nr. 8, date:8.2024: 3273-3290
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26620 |
The effectiveness of machine learning methods in the nonlinear coupled data assimilation
Enthalten in Geoscience Letters Bd. 11, 18.9.2024, Nr. 1, date:12.2024: 1-14
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