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In particular, this model is not based on Euclidean space and not on an infinite-precision arithmetic which lead to lacking numerical robustness and to topological inconsistency of implementations on a computer; it rests on a finite, discrete geometric domain called grid partition which takes into account finite-precision number systems available in computers.
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Conversely to the methodological approach proposed in literature, based on Multi Criteria Analysis giving different weights (affected by uncertainty) to TPIs, our methodological approach is based on Euclidean distance in a vector space ℜN, where N is the number of TPIs.
Therefore, the proposed approach does not give a weight to a TPI rather than another, and it is based on Euclidean distance in a vector space ℜN, where N is the number of TPIs.
In return, the time for projecting a test image onto the LOFESS space and matching based on Euclidean distance is less than one second, which is ideal for real-time applications.
The formation of clusters of samples inside this 3D space was analyzed by hierarchical clustering (based on Euclidean distance, average linkage and no additional scaling using the Matlab Bioinformatics Toolbox V3.2 Matlab™ [ 11]).
These functions were based on Euclidean distance function.
Conservation rankings based on movement data were uncorrelated with those based on Euclidean distance.
Clustering was based on Euclidean distance and average linkage.
Hierarchical clustering analysis was based on Euclidean distance metric and performed using R and Bioconductor software.
The molecular signature was illustrated with a heat map based on Euclidean distance (Figure 2).
The clustering algorithm was an agglomerative hierarchical method based on Euclidean distance of the average [31].
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