1. A non-transitory computer-readable medium having stored thereon computer-readable instructions that when executed by a computing device cause the computing device to: randomly select a first set of observation vectors from a training dataset, wherein a number of the first set of observation vectors is a predefined sample size; compute a first optimal value of an objective function defined for a support vector data description (SVDD) model using the selected first set of observation vectors to define a first set of support vectors, wherein the first set of support vectors define a first data description for the training dataset; (a) randomly select a second set of observation vectors from the training dataset, wherein a number of the second set of observation vectors is the predefined sample size; (b) compute a second optimal value of the objective function using the selected second set of observation vectors to define a second set of support vectors, wherein the second set of support vectors define a second data description for the training dataset; (c) update the first set of support vectors to include the defined second set of support vectors; (d) compute a third optimal value of the objective function using the updated first set of support vectors to define a third set of support vectors, wherein the third set of support vectors define a third data description for the training dataset; (e) compute a value of a stop parameter; (f) determine whether or not a stop condition is satisfied by comparing the computed value to a stop criterion; (g) when the stop condition is not satisfied, define the first set of support vectors as the defined third set of support vectors; and repeat (a)-(g) until the stop condition is satisfied; and when the stop condition is satisfied, output the defined third set of support vectors for identifying an outlier in a scoring dataset.