There are many methods introduced to solve the credit scoring problem such as support vector machines, neural networks and rule based classifiers. Rule bases are more favourite in credit decision making because of their ability to explicitly distinguish between good and bad applicants.In this paper multi-objective particle swarm is applied to optimize fuzzy apriori rule base in credit scoring. ...

Association rules are ”if-then rules” with two measures which quantify the support and confidence of the rule for a given data set. Having their origin in market basked analysis, association rules are now one of the most popular tools in data mining. This popularity is to a large part due to the availability of efficient algorithms. The first and arguably most influential algorithm for efficien...

We will discuss DF , the depth £rst implementation of APRIORI as devised in 1999 (see [8]). Given a database, this algorithm builds a trie in memory that contains all frequent itemsets, i.e., all sets that are contained in at least minsup transactions from the original database. Here minsup is a threshold value given in advance. In the trie, that is constructed by adding one item at a time, eve...

We investigate the application of Galois connections to the identi cation of frequent item sets, a central problem in data mining. Starting from the notion of closure generated by a Galois connection, we de ne the notion of extended closure, and we use these notions to improve the classical Apriori algorithm. Our experimental study shows that in certain situations, the algorithms that we descri...

The problem considered is that of finding frequent subpaths of a database of paths in a fixed undirected graph. This problem arises in applications such as predicting congestion in network traffic. An algorithm based on Apriori, called AFS, is developed, but with significantly improved efficiency through exploiting the underlying graph structure, which makes AFS feasible for practical input pat...

A Huge amount of data gets collected from society with different sources. Hardly has it led to a useful knowledge. For finding useful knowledge an algorithm is required. Apriori is an algorithm for mining data from databases which shows items that are related to each other. The databases having a size in GB and TB need a fast processor. For fast processing multicore processors are used. Paralle...

Parallel computing is a form of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently. Now Graphics Processing Unit (GPU) has taken a major role in high performance computing for generic applications. Compute Unified Device Architecture (CUDA) programming mo...