A
machine learning
system for
ranking a collection of filtered propensity to failure
metrics of like components within an
electrical grid that includes a
raw data assembly to provide
raw data representative of the like components within the
electrical grid; (b) a data processor, operatively coupled to the
raw data assembly, to convert the raw data to more uniform data via one or more
data processing techniques; (c) a
database, operatively coupled to the data processor, to store the more uniform data; (d) a
machine learning engine, operatively coupled to the
database, to provide a collection of propensity to failure
metrics for the like components; (e) an evaluation engine, operatively coupled to the
machine learning engine, to detect and remove non-complying
metrics from the collection of propensity to failure metrics and to provide the collection of filtered propensity to failure metrics; and (f) a decision support application, operatively coupled to the evaluation engine, configured to display a
ranking of the collection of filtered propensity to failure metrics of like components within the
electrical grid.