1. A computer implemented method comprising: normalizing sample data through transforming the sample data into a normalized value that is based, in part, on an identified average value for the sample data; binning the normalized value through transforming the normalized value into a binned value that is based, in part, on a predefined value range for a bin such that a bin value, within the predefined value range, exists for the sample data; identifying at least one vector value from the binned value; generating an entropy time series through transforming the at least one vector value into an entropy value to be displayed as part of a look-back window using the equation: H ⁡ ( E ) = - ∑ i = 1 v ⁢ ni n ⁢ log ⁢ ⁢ ni n where v is the total number of unique vector values in n samples and ni is the count vector value in the n samples; and using H(E) to generate an additional entropy time series represented by an additional equation: A = ∑ i = 1 c ⁢ Hi + ∏ i = 1 c ⁢ Hi where c represents at least one child node, and Hi represents H(E).