Your English writing platform
Discover LudwigSuggestions(5)
Exact(1)
The main division among variants is between MR and MR. The first evaluates distances between the pruned supertree and each input tree, while the second evaluates distances between the supertree and extended input trees.
Similar(59)
The last value produces an approximation of the joint distribution of two independent normal variates, whereas the setting with μ = 1 evaluates distance between a 'bivariate Cauchy' distribution and the distribution of two identically and independently distributed Cauchy random variables.
We use Ward's method [40] (uses an ANOVA approach to evaluate distances between clusters attempting to minimize at each step the sum of squares of any two (hypothetical) clusters that can be formed at each step) on our data set (normalized) to perform cluster analysis.
Standard methods such as K-means and hierarchical clustering evaluate distances between data points using all (equally weighted) features.
MDS enables one to easily visualize and evaluate distances between two objects considering at the same time the influence of all other objects.
Earth mover's distance is a method to evaluate distance between two multi-dimensional distributions by linear programming [44].
In goal programming approach, we use 1-norm distance (city-block distance) to evaluate distance between objective function and ideal point.
The quality of the consensus map was evaluated by comparing the locus arrangement of the consensus map with the arrangement of loci in the individual maps, and re-evaluating the distances between the markers, with a two-point independent analysis, in the consensus map using the 'two-point' command.
It uses an analysis of variance approach to evaluate the distances between clusters.
The Ward's method uses an analysis of variance approach to evaluate the distances between clusters in an attempt to minimize the sum of squares (SS) of any two clusters that can be formed at each step.
The ward's method makes use of an analysis of variance approach for evaluating the distances between clusters, in order to minimize the sum of squares (SS) of any two clusters that can be formed at each step (Willet 1987; Adams 1998; Otto 1998: Tziritis et al. 2016).
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com