Negative Association Rule Mining through Particle Swarm Optimization
نویسندگان
چکیده
Mining hidden pattern from existing databases is an important topic in field of data mining. The knowledge obtained from these databases is used in different applications like in market basket analysis. Association Rules are important to discover the relationships among the attributes in a database. In general the rules generated by Association Rule Mining technique do not consider the negative occurrences of attributes in them, but by focusing on infrequent items generated in system we can predict the rules which contains negative attributes. This paper proposes an improved algorithm NAPSO based on Particle Swarm Optimization. The algorithm improves result provided by apriori algorithm.
منابع مشابه
Particle swarm Optimization Based Association Rule Mining
Association rule mining is one of the widely using and simple concepts to find the frequent item sets from large number of datasets. While generating frequent item sets from a large dataset using association rule mining is not so efficient. This can be improved by using particle swarm optimization algorithm (PSO). PSO algorithm is population based evolutionary heuristic search methods used for ...
متن کاملAssociation Rules Optimization using Particle Swarm Optimization Algorithm with Mutation
In data mining, Association rule mining is one of the popular and simple method to find the frequent item sets from a large dataset. While generating frequent item sets from a large dataset using association rule mining, computer takes too much time. This can be improved by using particle swarm optimization algorithm (PSO). PSO algorithm is population based heuristic search technique used for s...
متن کاملS3PSO: Students’ Performance Prediction Based on Particle Swarm Optimization
Nowadays, new methods are required to take advantage of the rich and extensive gold mine of data given the vast content of data particularly created by educational systems. Data mining algorithms have been used in educational systems especially e-learning systems due to the broad usage of these systems. Providing a model to predict final student results in educational course is a reason for usi...
متن کاملA New Approach to Associative Classification Based on Binary Multi-objective Particle Swarm Optimization
Associative classification rule mining (ACRM) methods operate by association rule mining (ARM) to obtain classification rules from a previously classified data. In ACRM, classifiers are designed through two phases: rule extraction and rule selection. In this paper, the ACRM problem is treated as a multiobjective problem rather than a single objective one. As the problem is a discrete combinator...
متن کاملApplication of Weighted Particle Swarm Optimization in Association Rule Mining
Determination of the threshold values of support and confidence, affect the quality of association rule mining up to a great extent. Focus of my study is to apply weighted PSO for evaluating threshold values for support and confidence. The particle swarm optimization algorithm first searches for the optimum fitness value of each particle and then finds corresponding support and confidence as mi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013