A New Method for Generating All Positive and Negative Association Rules

Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 4

Abstract

Association Rule play very important role in recent scenario of data mining. But we have only generated positive rule, negative rule also useful in today data mining task. In this paper we are proposing “A new method for generating all positive and negative Association Rules” (NRGA).NRGA generates all association rules which are hidden when we have applied Apriori Algorithm. For representation of Negative Rules we are giving new name of this rules as like: CNR, ANR, and ACNR. In this paper we are also modify Correlation coefficient (CRC) equation, so all generate results are very promising. First we apply Apriori Algorithm for frequent itemset generation and that is also generate positive rules, after on frequent itemset we apply NRGA algorithm for all negative rules generation and optimize generated rules using Genetic Algorithm

Authors and Affiliations

Rupesh Dewang , Jitendra Agarwal

Keywords

Related Articles

Optimization of ETL Work Flow in Data Warehouse

ETL is responsible for extracting the information or data from different several Areas and applies some cleaning, customization, transformation function for data and finally loading into the data warehouse. This paper pr...

SEGMENTATION OF CT SCAN LUMBAR SPINE IMAGE USING MEDIAN FILTER AND CANNY EDGE DETECTION ALGORITHM

The lumbar vertebrae are the largest segments of the movable part of the vertebral column, they are elected L1 to L5, starting at the top. The spinal column, more commonly called the backbone, is made up primarily of ver...

Generalisation of RSA Scheme using fundamental groups and ZKIP

We address the problem of computation involved in RSA algorithm namely exponentiation under modulo arithmetic and various mathematical and timing attacks in RSA. The computation is made easy and quick by assigning elemen...

A SURVEY OF CALL MARKET (DISCRETE) AGENT BASED ARTIFICIAL STOCK MARKETS

Artificial stock markets are models of financial markets used to study and understand market dynamics. Agent Based Artificial Stock Markets can be seen as any market model in which prices are formed endogenously as a res...

Deriving Association between Urban and Rural Students Programming Skills

Data mining is used to extract the interesting patterns from databases or repositories. Frequent Pattern Tree is a technique for discovering association between the variables and finds the frequent patterns in the Studen...

Download PDF file
  • EP ID EP129517
  • DOI -
  • Views 86
  • Downloads 0

How To Cite

Rupesh Dewang, Jitendra Agarwal (2011). A New Method for Generating All Positive and Negative Association Rules. International Journal on Computer Science and Engineering, 3(4), 1649-1657. https://europub.co.uk/articles/-A-129517