Design and Development of Data Mining System to Estimate Cars Promotion using Improved ID3 Algorithm

Abstract: Now a day‟s customers are required comfort and their loving brand & color. With the arrival of the Internet and Data Mining Algorithms has definitely contributed to the altar of marketing focus. Here, we proposed Improved ID3 algorithm for best car market analysis. We are executed the similar in Weka Tool with Java code. We have analyzed the graphical performance study between ID3 and our novel improved ID3 clustering algorithms with Classes to Clusters evaluation purchase, safety, luggage booting, persons, doors, maintenance and buying attributes of customer‟s requirements for unacceptable/acceptable/good/very good ratings of a car to purchase. Conservative way of business is a challenging in car market due to many competitors are there around the world for providing aggressive products. The car manufacturers categorizes the car users and have to discover a suitable car; the seller correctly groups the buyers and he sells a right car; and the customers selects best car by analyzing more brands of cars with „N‟ number of sellers. These three cases they spent too much of time for analyzing old or statistical records for choosing a right product.

Keywords: Supervised Learning, Weka, Classification, ID3, Improved ID3.