Data Mining Algorithms And Applications

Data Mining is a new technique, which have become increasingly popular in recent years. People can apply the research result of knowledge discovery to the data process that can support the science decision. Now data mining has become a subject, which involved lots of science domain and technology especially in combining with Computational Intelligence (CI).Firstly, this paper introduces the basic concept, tasks, functions, applications and development way of data mining. Secondly, this paper introduces the basic concept, classification and classical algorithm ideas such as Apriori of association analysis. Then, one kind of binary association rules are proposed, and the special properties of this relation in function are charactered and the algorithm of finding the binary association rules are also presented. Clustering method is one of the core techniques in data mining. It was very important in data mining process. How to choose a clustering algorithm is decided by the clustering data, aim and application. A detailed comparison which involved usual clustering algorithm in data mining was given, and a comparing analysis of usual clustering algorithm including five synthetic evaluating criterion is also given. Based on it, an improved algorithm of K-Means is proposed, it can conquer disadvantage that customary algorithm is effected by the isolated point. Lastly, this paper introduces the basic concept, mathematical theory and technology in application of genetic algorithm. Then, a hybrid algorithm of clustering in terms of genetic algorithm and clustering analysis is proposed. The new algorithm well improves clustering algorithm.