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The main difference of the associative classification algorithms is how to mine frequent item sets, analyze the rules exported and use for classification. This paper presents an associative classification algorithm based on Trie-tree that named CARPT, which remove the frequent items that cannot generate frequent rules directly by adding the count of class labels. And we compress the storage of database...
Classification rules are the interest of most data miners to summarize the discrimination ability of classes present in data. A classification rule is an assertion, which discriminates the concepts of one class from other classes. The most classification rules mining algorithm aims to providing a single solution where multiple solutions exist. Moreover, it does not guarantee the optimal solution and...
The classification algorithm based on association rules (CBA) has a good performance in many data sets. At present, there are not many people using classification algorithm to analyze the data of labor market. In this paper, we use CBA algorithm to classify the dataset of the labor market. Then we, by using classification results, make a deeper research to submit a more rational calculation of the...
It is necessary to discrete datasets firstly if you want to data mining an association rule of datasets consisting of many categorical and numeric attributes by a traditional algorithm. However, in view of the versatility, the applications of the traditional algorithm are limited. This paper propose a new algorithm called ARMFI(Association Rule of Multiple Frequent Item-sets) which can data mining...
CBA is a classification algorithm integrating association rule mining and classification. CBA has been widely used in data mining areas because it has higher accuracy than C4.5. When the samples become more and more large and characteristic attributes become more and more numerous, CBA algorithm becomes much lower. In this paper, an improved CBA algorithm based on rough set is proposed. The improved...
Intrusion detection is one of network security area of technology main research directions. Data mining technology was applied to network intrusion detection system (NIDS), may automatically discover the new pattern from the massive network data, to reduce the workload of the manual compilation intrusion behavior patterns and normal behavior patterns. This article reviewed the current intrusion detection...
Management of data imprecision and uncertainty has become increasingly important, especially in situation awareness and assessment applications where reliability of the decision-making process is critical (e.g., in military battlefields). These applications require the following: 1) an effective methodology for modeling data imperfections and 2) procedures for enabling knowledge discovery and quantifying...
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