Results 41 to 50 of about 17,286,028 (305)
, 2023 Precision-Recall curves (a) the proposed CNN model+random forest classifier (b) the proposed CNN model+logistic regression classifier (c) tuned MobileNetV2 + random forest classifier.
Ahmad Salah (9034673) +3 more
core +1 more source
ASSOCIATION RULES IN RANDOM FOREST FOR THE MOST INTERPRETABLE MODEL
Barekeng, 2023 Random forest is one of the most popular ensemble methods and has many advantages. However, random forest is a "black-box" model, so the model is difficult to interpret.
Hafizah Ilma +2 more
doaj +1 more source
Random-effects model forest plots showing the impact of autologous BT on PCa survival after RP.
, 2017 Random-effects model forest plots showing the impact of autologous BT on PCa survival after RP.
Su-Liang Li (3704542) +2 more
core +1 more source
, 2023 Confusion matrices (a) the proposed CNN model+random forest classifier (b) the proposed CNN model+logistic regression classifier (c) tuned MobileNetV2 + random forest classifier.
Ahmad Salah (9034673) +3 more
core +1 more source
From mice to humans—divergent strategies for intestinal homeostasis and regeneration
FEBS Letters, EarlyView.Recent advances such as organoid genome editing, xenotransplantation, imaging, and whole‐genome sequencing have enabled direct studies of human intestinal stem cells (ISCs). These studies reveal species‐specific features, including slower ISC proliferation, distinct injury responses, slower somatic mutation accumulation in humans, and an inverse ...
Keiko Ishikawa +2 more
wiley +1 more source
Statistical Downscaling of Temperature with the Random Forest Model
Advances in Meteorology, 2017 The issues with downscaling the outputs of a global climate model (GCM) to a regional scale that are appropriate to hydrological impact studies are investigated using the random forest (RF) model, which has been shown to be superior for large dataset ...
Bo Pang +3 more
doaj +1 more source
Geological structure recognition model based on improved random forest algorithm
Meitan kexue jishu, 2023 Seismic attributes are often used for structural interpretation and prediction. In order to overcome the problems of multiple solutions and uncertainty caused by single seismic attribute prediction, seismic multi-attribute fusion technology is used to ...
Huaixiu WANG, Siyi FENG, Zuiliang LIU
doaj +1 more source
FEBS Letters, EarlyView.Vacuolar H+‐ATPase (V‐ATPase) is a multisubunit rotary proton pump that acidifies intracellular compartments. Using elastic network models, we identified conserved hinge residues that govern its large‐scale functional motions. We show that intrinsically encoded ‘soft modes’ drive critical functional transitions, including rotary catalysis and ...
Diksha Parwana +3 more
wiley +1 more source
Reservoir Parameter Prediction Based on the Neural Random Forest Model
Frontiers in Earth Science, 2022 Porosity and saturation are the basis for describing reservoir properties and formation characteristics. The traditional, empirical, and formulaic methods are unable to accurately capture the nonlinear mapping relationship between log data and reservoir ...
Mingchuan Wang +3 more
doaj +1 more source
Seed classification with random forest models
Applications in Plant SciencesAbstractPremiseTo improve forest conservation monitoring, we developed a protocol to automatically count and identify the seeds of plant species with minimal resource requirements, making the process more efficient and less dependent on human operators.Methods and ResultsSeeds from six North American conifer tree species were separated from leaf litter
Josephine Elena Reek +3 more
openaire +4 more sources