Facilitating interpretation of high-dimensional data clusters

A computing device to interpret clusters of high-dimensional data, comprising:

• a processor;
• a memory storing machine readable instructions that are to cause the processor to:
• project the high-dimensional data to a multi-dimensional space to display clusters of the high-dimensional data;
• derive a normalized attribute dissimilar measure to calculate a plurality of dissimilar attributes from at least a pair of clusters selected by a user;
• is display the plurality of dissimilar attributes for a user to select a dissimilar attribute from the plurality of dissimilar attributes;
• in response to receipt of the user selection of the dissimilar attribute, determine a plurality of correlated attributes that are correlated to the dissimilar attribute;
• and
• reproject the plurality of dissimilar attributes to the multi-dimensional space using a set of the plurality of dissimilar attributes.

A non-transitory computer readable medium to interpret clusters of high-dimensional data, including machine readable instructions executable by a processor to;

• project the high-dimensional data to a multi-dimensional space to display clusters of the high-dimensional data;
• receive a selection of at least two of the plurality of clusters;
• calculate a number of most dissimilar dimensions from the at least two selected clusters, wherein the number of most dissimilar dimensions have a highest difference distribution among all dimensions of the at least two selected clusters;
• receive a selection of a dissimilar dimension from the number of most dissimilar dimensions;
• calculate a number of most correlated dimensions to the selected dissimilar dimension, wherein the most correlated dimensions have a highest correlation distribution the selected dimension among all dimensions of the at least two selected clusters;
• and
• display the plurality of most dissimilar dimensions and the plurality of most correlated dimensions.