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1 |
Mixed-integer linear optimization for cardinality-constrained random forests
Enthalten in Optimization letters 10.5.2025: 1-19
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2 |
Exploring the predictors of the populist vote using random forests
Enthalten in Quality & quantity 11.2.2025: 1-34
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3 |
Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA
Arasteh-Khoshbin, Omolbanin. - Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2024
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4 |
First-Fit Coloring of Forests in Random Arrival Model
Bosek, Bartłomiej. - Wadern : Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2024
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5 |
Random forests for survival data: which methods work best and under what conditions?
Enthalten in The international journal of biostatistics Bd. 20, 2024, Nr. 2: 315-345. 31 S.
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6 |
Erratum to “Random forest and artificial neural network-based tsunami forests classification using data fusion of Sentinel-2 and Airbus Vision-1 satellites: A case study of Garhi Chandan, Pakistan”
Enthalten in Open Geosciences Bd. 16, 2024, Nr. 1. 1 S.
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7 |
Random forest and artificial neural network-based tsunami forests classification using data fusion of Sentinel-2 and Airbus Vision-1 satellites: A case study of Garhi Chandan, Pakistan
Enthalten in Open Geosciences Bd. 16, 2024, Nr. 1. 25 S.
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8 |
Construction and Application of a Pollen Emissions Model based on Phenology and Random Forests
Enthalten in EGUsphere 19.09.2024: 1-41. 41 S.
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9 |
Using Random Forests to Predict Extreme Sea-Levels at the Baltic Coast at Weekly Timescales
Enthalten in EGUsphere 13.08.2024: 1-52. 52 S.
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10 |
Managing Seismic Risk Associated to Development Blasting Using Random Forests Predictive Models Based on Geologic and Structural Rockmass Properties
Enthalten in Rock mechanics and rock engineering 25.6.2024: 1-22
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