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In Data Mining and Machine Learning, the missing attribute will have a negative impact on the learning results. The filling of missing values is a very challenging work. In this paper, a new algorithm based on gray relational analysis is presented, which takes the differences of the relationships between the properties into account. When calculating the gray relational grade, the weights of attributes...
In order to avoid redundant calculation and reduce the time of scanning database, this paper proposes an algorithm of association rules mining based on digit sequence (DS). The algorithm firstly turns all transactions into digital transactions by binary, and then computing digit sequence of every attribute item. Finally, the algorithm uses forming digital pure subset of digital transaction to generate...
In this paper, in order to improve the method of computing support of candidate frequent itemsets, in order to reduce the times of scanning database when computing support, and in order to fast search long frequent itemsets, aiming to top-down search strategy, we propose an improved top-down association rules mining algorithm based on sequence number, which is suitable for mining long frequent itemsets...
In order to reduce redundant candidate itemsets and repeated computing existing in these presented double search mining algorithms, this paper proposes an algorithm of double search association rules mining based on digital complementary sets, which adopts two methods of forming candidate itemsets to fast execute double searching, the way of generating subsets of non frequent itemsets is used to down...
This paper proposes an efficient algorithm of double search mining association rules based on digital pure subset, which uses the method of forming digital pure subset of transaction to generate candidate itemsets, and uses digital character to reduce the number of scanned transactions when computing support of itemsets after these transactions are turned into digital transaction by binary. In addition,...
In this paper, in order to reduce the times of scanning database when presented algorithms compute support of candidate frequent itemsets, in order to improve the method of computing support of candidate frequent itemsets, and in order to further improve the efficiency of algorithm, based on up search strategy of Apriori, we propose an algorithm of association rules mining based on sequence number...
There are excessive and disordered rules generated by traditional approaches of association rule mining, many of which are redundant, so that they are difficult for users to understand and make use of. Han et al pointed out the bottleneck of association rules mining is not on whether we can derive the complete set of rules under certain constraints efficiently but on whether we can derive a compact...
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