Chart the original Euclidean distances between data points (x-axis) versus Euclidean distances in reduced 2-dimensional space. The Spearman's rank correlation coefficient is shown.
This blog post describe the interpretation of plots with dimension reduction performed by different algorithms.
Note that t-SNE is particularly sensitive to the choice of random seed (which can be amended via the R code) and consequently the t-SNE correlation coefficient may vary depending on the seed.
Example
Example output:
Input Example:
An analysis using t-SNE, MDS, or PCA.
Options
Dimension Reduction An R Output containing a principal components, multidimensional scaling or t-SNE analysis.
Maximum points The maximum number of points to plot. If the object contains more data points, a random sample is taken.
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