Sentence examples for three dimensional data space from inspiring English sources

Conceptually, this can be perceived as a cylinder of varying radius and length that scans a through three dimensional data – space on the horizontal axis and time on the vertical axis.

To cluster the proteins according to the codon usage data we used an unsupervised clustering method analysis, SOM, which is a clustering method based on neural networks, and it helps to visualize datasets by mapping a high dimensional data space into a two dimensional space [ 26].

Multifractals analyze the scaling properties of quantities distributed in a space that we assume to be two dimensional (a plane), but MFA can be used with one dimensional (time series) or three dimensional data.

PCA, a well-known multivariate data reduction technique, projects the correlated higher dimensional data space into uncorrelated lower dimensional components using an orthogonal transformation.

Lower dimensional data spaces are easier to visualize and interpret.

Given a three-dimensional data space, much data are in the third and eighth quadrants.

In the original high-dimensional data space, the nearest neighbour error was 10.

SOM implements nonlinear projection of multidimensional data onto a two-dimensional array of weight vectors, and this effectively preserves the topology of the high-dimensional data space [ 8– 10].

Factor analysis assumes that the high-dimensional data spaces x and y have been generated by low-dimensional latent variable spaces x lat and x lat, respectively.

Traditional techniques for visualization methods convert high-dimensional data into two or three dimensional metric spaces [ 11], and construct one single map for visualizing objects.

In future work, an effort will be made to project the data in the three dimensional space, or exploit the concept of multi-level 2.5D network representation [ 29].