For predictions we have two types of modeling, a regression type and classification type.
Regression modeling deals with predicting “y” values that are continuous like age, outage_cost, outage_minutes while classification modeling deals with predicting “y” values that are discrete (nominals) like gender, outage month, feeder etc.
In regression the accuracy often used is Mean Absolute Error which gives out the average of error calculated as the difference between actual value and predicated value.
In classification the accuracy often used is the percentage of correct values.
