International Journal of Innovative Science Engineering and Technology (IJISET)
Data mining is widely done in recent times to predict results from the existing wide range of data that fits their research. On this basis a voting data base is studied to find out the interest of the voters among the attributes given using the some associative rule data mining algorithms. The association rule algorithm studies the frequent items that are being used in the data base. A comparative study of the associate rule (FP-Growth & Apriori) algorithms is used on the voter data set and the results are compared in this paper.