In this paper we apply data-mining techniques to a classication problemon actual electricity consumption data from 350 Swedish households. Morespecically we use measurements of hourly electricity consumption during one monthand t classication models to the given data. The goal is to classify and later predict whether the building type of a specic household is an apartmentor a detached house. This classication/prediction problem becomes important ifone has a consumption time series for a household with unknown building type. Tocharacterise each household, we compute from the data some selected statistical attributesand also the load prole throughout the day for that household. The most important task here is to select a good representative set of feature variables, whichis solved by ranking the variable importance using technique of random forest. Wethen classify the data using classication tree method and linear discriminant analysis.The predictive power of the chosen classication models is plausible.