11. The method of claim 10 , further comprising communicating output from at least one of the machine learning results evaluator and the system performance evaluator to a unified user interface.
10. A method for evaluating the accuracy of a predicted effectiveness of an improvement to an infrastructure based on data collected from the infrastructure during a first time period before a change to an infrastructure has been implemented and a second time period after the change to the infrastructure has been implemented, the collected data including information representative of at least one pre-defined metric of the infrastructure, comprising: (a) collecting data from the infrastructure during the first time period and the second time period, wherein the data meets at least one predetermined threshold requirement; (b) compiling the collected data to generate compiled data representative of the first time period and compiled data representative of the second time period; (c) providing the compiled data to a machine learning system if the compiled data meets the at least one predetermine threshold requirement; (d) performing machine learning on the compiled data representative of the first time period and generating corresponding machine learning data; (e) storing and empirically evaluating the generated machine learning data; (f) implementing the change to the infrastructure, wherein the change to the infrastructure is based at least in part on the generated machine learning data, and (g) receiving the compiled data representative of the first time period and the compiled data representative of the second time period therefrom, for: (i) comparing the compiled data representative of the first time period to the compiled data representative of the second time period to determine a difference, if any, and (ii) comparing the difference, if any, determined in (i) to a prediction based on the generated machine learning data.