A Combined Approach of Data Mining Algorithms Based on Association Rule Mining and Rule Induction
Amarjeet Kaur1, Kumar Saurabh2, Gurpreet Singh3
1Er. Amarjeet Kaur, Research Scholar, RIET, Phagwara (Punjab) India.
2Er. Kumar Saurabh, AP(IT), Department of Computer Science & Engg. Ramgarhia Institute of Engg & Management Technology, Phagwara India.
3Er. Gurpreet Singh, Assistant Professor & Head, Department of Computer Science & Engg. St. Soldier Institute of Engg. & Technology, Jalandhar (Punjab) India.
Manuscript received on October 22, 2013. | Revised Manuscript received on November 03, 2013. | Manuscript published on November 05, 2013. | PP: 61-62 | Volume-3 Issue-5, November 2013 . | Retrieval Number: E1885113513 /2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Association rule learning is a popular method for discovering interesting relations between variables in large database. It is often used in market basket analysis domain e.g. if a customer buys onions and potatoes then he buys also beef. But, in fact, it can be implemented in various application areas where we want to discover the association between variables. The A PRIORI approach is certainly the most popular[1]. But, despite its good properties, this method has a drawback: the number of obtained rules can be very high. The ability to underline the most interesting rules, those which are relevant, becomes a major challenge. In this research work titled a hybrid approach based on Association Rule mining and Rule Induction in Data Mining we using induction algorithms and Association Rule mining algorithms as a hybrid approach to maximize the accurate result in fast processing time. This approach can obtain better result than previous work. This can also improves the traditional algorithms with good result. In the above section we will discuss how this approach results in a positive as compares to other approaches.
Keywords: Association Rule mining, A priori algorithm, Rule Induction, Decision list induction, Data mining.