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A survey on missing data in machine learning
Abstract Machine learning has been the corner stone in analysing and extracting information
from data and often a problem of missing values is encountered. Missing values occur …
from data and often a problem of missing values is encountered. Missing values occur …
Reforms: Consensus-based recommendations for machine-learning-based science
Machine learning (ML) methods are proliferating in scientific research. However, the
adoption of these methods has been accompanied by failures of validity, reproducibility, and …
adoption of these methods has been accompanied by failures of validity, reproducibility, and …
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 …
Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling
The use of correlative ecological niche models has highly increased in the last decade.
Despite all literature and textbooks in this field, few practical guidelines exist on the correct …
Despite all literature and textbooks in this field, few practical guidelines exist on the correct …
Species distribution models rarely predict the biology of real populations
Species distribution models (SDMs) are widely used in ecology. In theory, SDMs capture (at
least part of) species' ecological niches and can be used to make inferences about the …
least part of) species' ecological niches and can be used to make inferences about the …
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
Background To evaluate binary classifications and their confusion matrices, scientific
researchers can employ several statistical rates, accordingly to the goal of the experiment …
researchers can employ several statistical rates, accordingly to the goal of the experiment …
[HTML][HTML] Accuracy assessment in convolutional neural network-based deep learning remote sensing studies—Part 1: Literature review
Convolutional neural network (CNN)-based deep learning (DL) is a powerful, recently
developed image classification approach. With origins in the computer vision and image …
developed image classification approach. With origins in the computer vision and image …
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 …
Top ten hazards to avoid when modeling species distributions: a didactic guide of assumptions, problems, and recommendations
M Soley‐Guardia, DF Alvarado‐Serrano… - Ecography, 2024 - Wiley Online Library
Species distribution models, also known as ecological niche models or habitat suitability
models, have become commonplace for addressing fundamental and applied biodiversity …
models, have become commonplace for addressing fundamental and applied biodiversity …
Impact of 2019–2020 mega-fires on Australian fauna habitat
Abstract Australia's 2019–2020 mega-fires were exacerbated by drought, anthropogenic
climate change and existing land-use management. Here, using a combination of remotely …
climate change and existing land-use management. Here, using a combination of remotely …