期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2016
卷号：5
期号：3
页码：15976-15979
DOI：10.18535/ijecs/v5i3.16
出版社：IJECS
摘要：Data mining is the task of discovering useful and interested patterns from the huge amount of the data where the data can be stored indatabases, data warehouses and other information repositories. Data mining comprises an integration of techniques from various disciplinessuch as data visualization, database technology, information retrieval, high performance computing, machine learning and pattern recognition,etc. The classification of multi-dimensional data is one of the major challenges in data mining and data warehousing. In a classificationproblem, each object is defined by its attribute values in multidimensional space. Some of the existing systems consider the data analysis mightidentify the set of candidate data cubes for exploratory analysis based on domain knowledge. Unfortunately, conditions occurred for suchassumptions are not valid and these include high dimensional databases, which are difficult or impossible to pre-calculate the dimensions andcubes. Some proposed system is formulated automatically find out the dimensions and cubes, which holds the informative and interesting data.In high dimensional datasets, the data analysis procedures need to be integrated with each other. Based on the information theoretic measureslike Entropy is used to filter out the irrelevant data from the dataset in order to formulate a more compact, manageable and useful schema
关键词：Data Mining; Risk Prediction; Association Rule; Information Gain
