Point process models for presence‐only analysis
Presence‐only data are widely used for species distribution modelling, and point process
regression models are a flexible tool that has considerable potential for this problem, when …
regression models are a flexible tool that has considerable potential for this problem, when …
Caveats for correlative species distribution modeling
Correlative species distribution models are becoming commonplace in the scientific
literature and public outreach products, displaying locations, abundance, or suitable …
literature and public outreach products, displaying locations, abundance, or suitable …
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification
Binary classification is a common task for which machine learning and computational
statistics are used, and the area under the receiver operating characteristic curve (ROC …
statistics are used, and the area under the receiver operating characteristic curve (ROC …
The global distribution of known and undiscovered ant biodiversity
Invertebrates constitute the majority of animal species and are critical for ecosystem
functioning and services. Nonetheless, global invertebrate biodiversity patterns and their …
functioning and services. Nonetheless, global invertebrate biodiversity patterns and their …
Urban flood risk map** using the GARP and QUEST models: A comparative study of machine learning techniques
Flood risk map** and modeling is important to prevent urban flood damage. In this study,
a flood risk map was produced with limited hydrological and hydraulic data using two state …
a flood risk map was produced with limited hydrological and hydraulic data using two state …
kuenm: an R package for detailed development of ecological niche models using Maxent
Background Ecological niche modeling is a set of analytical tools with applications in
diverse disciplines, yet creating these models rigorously is now a challenging task. The …
diverse disciplines, yet creating these models rigorously is now a challenging task. The …
Paintings predict the distribution of species, or the challenge of selecting environmental predictors and evaluation statistics
Y Fourcade, AG Besnard… - Global Ecology and …, 2018 - Wiley Online Library
Aim Species distribution modelling, a family of statistical methods that predicts species
distributions from a set of occurrences and environmental predictors, is now routinely …
distributions from a set of occurrences and environmental predictors, is now routinely …
Minimum required number of specimen records to develop accurate species distribution models
Species distribution models (SDMs) are widely used to predict the occurrence of species.
Because SDMs generally use presence‐only data, validation of the predicted distribution …
Because SDMs generally use presence‐only data, validation of the predicted distribution …
The area under the precision‐recall curve as a performance metric for rare binary events
Species distribution models are used to study biogeographic patterns and guide decision‐
making. The variable quality of these models makes it critical to assess whether a model's …
making. The variable quality of these models makes it critical to assess whether a model's …
Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU
Background Early and accurate identification of sepsis patients with high risk of in-hospital
death can help physicians in intensive care units (ICUs) make optimal clinical decisions …
death can help physicians in intensive care units (ICUs) make optimal clinical decisions …