Results 11 to 20 of about 16,649 (216)

Variable importance‐weighted Random Forests [PDF]

Quantitative Biology, 2017
BackgroundRandom Forests is a popular classification and regression method that has proven powerful for various prediction problems in biological studies. However, its performance often deteriorates when the number of features increases. To address this limitation, feature elimination Random Forests was proposed that only uses features with the largest
Yiyi Liu, Hongyu Zhao 0003
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Identifying HIV sequences that escape antibody neutralization using random forests and collaborative targeted learning

Journal of Causal Inference, 2022
Recent studies have indicated that it is possible to protect individuals from HIV infection using passive infusion of monoclonal antibodies. However, in order for monoclonal antibodies to confer robust protection, the antibodies must be capable of ...
Jin Yutong, Benkeser David
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Investigating the Effects of Cell Size in Statistical Landslide Susceptibility Modelling for Different Landslide Typologies: A Test in Central–Northern Sicily

Applied Sciences, 2023
Optimally sizing grid cells is a relevant research issue in landslide susceptibility evaluation. In fact, the size of the adopted mapping units influences several aspects spanning from statistical (the number of positive/negative cases and prevalence and
Chiara Martinello, Chiara Cappadonia, Edoardo Rotigliano   +2 more
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Conditional variable importance for random forests [PDF]

BMC Bioinformatics, 2008
Random forests are becoming increasingly popular in many scientific fields because they can cope with ``small n large p'' problems, complex interactions and even highly correlated predictor variables. Their variable importance measures have recently been suggested as screening tools for, e.g., gene expression studies. However, these variable importance
Carolin Strobl, Anne-Laure Boulesteix, Thomas Kneib, Thomas Augustin 0001, Achim Zeileis   +4 more
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Improved Estimation of Winter Wheat Aboveground Biomass Using Multiscale Textures Extracted from UAV-Based Digital Images and Hyperspectral Feature Analysis

Remote Sensing, 2021
Rapid and accurate crop aboveground biomass estimation is beneficial for high-throughput phenotyping and site-specific field management. This study explored the utility of high-definition digital images acquired by a low-flying unmanned aerial vehicle ...
Yuanyuan Fu, Guijun Yang, Xiaoyu Song, Zhenhong Li, Xingang Xu, Haikuan Feng, Chunjiang Zhao   +6 more
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Remote Sensing Supported Sea Surface pCO₂ Estimation and Variable Analysis in the Baltic Sea

Remote Sensing, 2021
Marginal seas are a dynamic and still to large extent uncertain component of the global carbon cycle. The large temporal and spatial variations of sea-surface partial pressure of carbon dioxide (pCO2) in these areas are driven by multiple complex ...
Shuping Zhang, Anna Rutgersson, Petra Philipson, Marcus B. Wallin   +3 more
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Combination of Landsat 8 OLI and Sentinel-1 SAR Time-Series Data for Mapping Paddy Fields in Parts of West and Central Java Provinces, Indonesia

ISPRS International Journal of Geo-Information, 2020
The rise of Google Earth Engine, a cloud computing platform for spatial data, has unlocked seamless integration for multi-sensor and multi-temporal analysis, which is useful for the identification of land-cover classes based on their temporal ...
Sanjiwana Arjasakusuma, Sandiaga Swahyu Kusuma, Raihan Rafif, Siti Saringatin, Pramaditya Wicaksono   +4 more
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Improving Explainability of Major Risk Factors in Artificial Neural Networks for Auto Insurance Rate Regulation

Risks, 2021
In insurance rate-making, the use of statistical machine learning techniques such as artificial neural networks (ANN) is an emerging approach, and many insurance companies have been using them for pricing.
Shengkun Xie
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Key predisposing factors and susceptibility assessment of landslides along the Yunnan–Tibet traffic corridor, Tibetan plateau: Comparison with the LR, RF, NB, and MLP techniques

Frontiers in Earth Science, 2023
The Yunnan–Tibet traffic corridor runs through the Three Rivers Region, southeastern Tibetan Plateau, which is characterized by high-relief topography and active tectonics, with favourable conditions for landslides.
Sen Wang, Sixiang Ling, Sixiang Ling, Xiyong Wu, Xiyong Wu, Hong Wen, Hong Wen, Junpeng Huang, Feng Wang, Chunwei Sun   +9 more
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The Importance of Variable Importance

, 2022
32 ...
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