Mining Himachal Pradesh State Electricity Board for AT&C Losses with Data Mining Association Rules?

The leading business challenges faced by the technical world today in business field are rightful extraction of information from huge data bases and its application into future ventures to minimise the losses, maximize the profits, and multiply the dividends. In this direction data mining and its tools prove useful in extracting each and every hidden and relevant piece of information. This paper presents an empirical study on data of Himachal Pradesh State Electricity Board to find out reasons and regions of the major AT&C losses for the current years’ eight months for three towns. This work is accomplished with the help of data mining association rules generated with Apriori and verified Predictive Apriori algorithm’s results. The performance of these two relative algorithms on nominal datasets is also comparatively concluded in the end.