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11 |
Random survival forests with competing events: a subdistribution‐based imputation approach
Behning, Charlotte. - Freiburg : Universität, 2024
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12 |
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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13 |
Seeing the wood for the trees: predictive margins for random forests
Enthalten in Corpus linguistics and linguistic theory Bd. 20, 2024, Nr. 1: 153-181. 29 S.
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14 |
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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15 |
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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16 |
Random Forests with Economic Roots: Explaining Machine Learning in Hedonic Imputation
Enthalten in Computational economics 26.11.2024: 1-25
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17 |
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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18 |
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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19 |
Using Three-dimensional Modeling and Random Forests to Predict Deep Ore Potentials: A Case Study on Xiongcun Porphyry Copper–Gold Deposit in Tibet, China
Enthalten in Mathematical geosciences 29.7.2024: 1-29
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20 |
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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