I have a work order system. I found out that the work order completion times are exponentially distributed. Every ticket has some features. I understand that regression is "a line that best fits the points". In my case, I want the line to be exponential curve. Is it possible ? Or is CDF for exponential distribution better option ?
My use case is I want to predict the probability of a work order completing by deadline. I was thinking of querying sets of data through "group by" & then compute and store the lambda parameters. When a new ticket comes in, I will pull the corresponding lambda & use CDF to determine %age. I am wondering if an ML algorithm can simplify this process.
I have .net stack. I use Accord.net. I'm open to other .net libs.