Abstract—Risk taking capability of a person in the financial market is based on many factors including demographic factors like age, education, marital status etc. In this paper in order to analyze the various investment instruments used by the people of different profiles; we have applied fuzzy data mining technique to the demographic factors of a human being. After the division into fuzzy clusters, membership of the person to the clusters is calculated. After the memberships, the derived memberships are used to find the people those have the memberships in the similar range. The result is in the form of investment patterns of the similar people .In further processing the FP growth is applied to find the most recurring patterns. The process sequence for the same has been shown in the paper through the example of five input sets. The main aim of this paper is to apply data mining to find the investment patterns of a person based on their characteristic.

Index Terms—Fuzzy c means, frequent pattern growth, data mining.

The authors are with Department of Computer Science /Information Technologg, Jaypee Institute of Information Technology, Noida, India (email: sakshisingh29@gmail.com, harsh5890@gmail.com, archana.purwar@jiit.ac.in).

Cite:Sakshi Singh, Harsh Mittal, and Archana Purwar, "Prediction of Investment Patterns Using Data Mining Techniques," International Journal of Computer and Communication Engineering vol. 3, no. 2, pp. 145-148, 2014.