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7 results for “Distance Metrics”
Euclide, the crow, the wolf and the pedestrian: distance metrics for linguistic typology - Dataset
<p>This repository contains the distance matrices and code for the paper "Euclide, the crow, the wolf and the pedestrian: distance metrics for linguistic typology"</p>
Data from: The article Euclimatch: An R package for climate matching with Euclidean distance metrics
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A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics
<p>The dataset is based on the paper: </p> <p>Hoang-Son Pham, Hanne Poelmans and Amr Ali-Eldin ‘’A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics’’, IEEE Access (2023).</p> <p>The dataset includes: </p> <p>1. a list of project metadata extracted from FRIS portal</p> <p>2. a list of VODS disciplines</p> <p>3. a distance matrix</p> <p> </p> <p>* Kindly refer to our paper for more details on the dataset.</p> <p>https://ieeexplore.ieee.org/document/10156853</p>
DataSet for UAV-based Untrained Small Object Detection using Distance Metric Method
<p>DataSet for UAV-based Untrained Small Object Detection using Distance Metric Method</p>
FIG. 2. Nonmetric multidimensional scaling calculated with the Bray-Curtis distance metric using a in Spatial Variation of False Map Turtle (Graptemys pseudogeographica) Bacterial Microbiota in the Lower Missouri River, United States
FIG. 2. Nonmetric multidimensional scaling calculated with the Bray-Curtis distance metric using a square root transformation and Wisconsin double-standardization. Location is represented by color, and sex is represented by shape. Stress of fit for the ordination is reported at 0.145. Axis titles represent the two dimensions to which the data have been ordinated.
Data from: A comparison of individual-based genetic distance metrics for landscape genetics
A major aim of landscape genetics is to understand how landscapes resist gene flow and thereby influence population genetic structure. An empirical understanding of this process provides a wealth of information that can be used to guide conservation and management of species in fragmented landscapes, and also to predict how landscape change may affect population viability. Statistical approaches to infer the true model among competing alternatives are based on the strength of the relationship between pairwise genetic distances and landscape distances among sampled individuals in a population. A variety of methods have been devised to quantify individual genetic distances, but no study has yet compared their relative performance when used for model selection in landscape genetics. In this study, we used population genetic simulations to assess the accuracy of 16 individual-based genetic distance metrics under varying sample sizes and degree of population genetic structure. We found most metrics performed well when sample size and genetic structure was high. However, it was much more challenging to infer the true model when sample size and genetic structure was low. Under these conditions, we found genetic distance metrics based on principal components analysis were the most accurate (though several other metrics performed similarly), but only when they were derived from multiple principal component axes (the optimal number varied depending on the degree of population genetic structure). Our results provide guidance for which genetic distance metrics maximize model selection accuracy and thereby better inform conservation and management decisions based upon landscape genetic analysis.
Data from: A comparison of individual-based genetic distance metrics for landscape genetics
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.