Sentence examples for multidimensional distance from inspiring English sources

For the two test areas a total of 3500 different configurations of the k-NN algorithm were systematically tested by changing the number and type of spectral and ancillary input variables, type of multidimensional distance measures, number of nearest neighbors and methods for spectral feature extraction using the leave-one-out (LOO) procedure.

Note that the multidimensional distance defined in equation 1 is used.

Various multidimensional distance metrics are known, but necessary computational resources tend to scale with the number of bins raised to some large power.

When two odors are compared for their valence, this comparison is highly correlated with the similarity of their across-glomerular patterns (either as Euclidean distance in a multidimensional space, or as their angular distance, which is the correspondent, intensity-invariant measure) (Parnas et al., 2013).

Euclidean distance It simply is a geometric distance in a multidimensional space.

We formulate and prove a lemma that crisp memberships are a necessary consequence of the topology of the multidimensional space of pair-distance standard deviations.

Many non-parametric classification algorithms in machine learning such as k-nearest neighbors (k-NN) perform poorly in a multidimensional space where pairwise distances between input datapoints become large.

We computed the correlations between gene pair-wise Euclidean distances in multidimensional space and in their configuration in a 2D network layout.

Finally, plotting the distances in multidimensional space between detector models and activation patterns across all areas, Figure 3c confirms that L frontotemporal regions have the closest links to the inflectional model while bilateral temporal regions are closer to the phrasal model (for details see Table S4, Supporting Information).

Cluster analysis reveals dissimilarities between cells by calculating the intercellular distance in a multidimensional space, where each dimension corresponds to one of the quantified cellular parameters.

In a first step, we demonstrate that our vectorial representation of RNA structures and the Euclidian distance in the multidimensional space consequently defined is comparable with the sequence/structure similarities identified by LocARNA a conventional structural clustering method.