نتایج جستجو برای: data mining association rules k means algorithm a priori algorithm
تعداد نتایج: 14071376 فیلتر نتایج به سال:
Association rule mining is the most popular technique in the area of data mining. The main task of this technique is to find the frequent patterns by using minimum support thresholds decided by the user. The Apriori algorithm is a classical algorithm among association rule mining techniques. This algorithm is inefficient because it scans the database many times. Second, if the database is large...
Introduction: About 10-15 percent of Iranian couples are infertile which is due to different causes determining particular diagnostic and treatment methods. In this study, the model presented is based on basic features and simple tests, helping physicians predict the causes of infertility Methods: The data were taken from Sarem hospital infertility data bank by using data mining methods. ...
Mining for association rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an efficient algorithm for mining association rules that is faster than the previously proposed partition algorithms approximately m times where m is the number of stages in pipeline. The algorithm is also ideally suited for pa...
A comparison of mining association rules from clusters generated by qualitative clustering and clusters obtained by quantitative clustering is presented. Whereas in quantitative clustering only numerical data are included, numerical and categorical data are used in qualitative clustering for record conglomeration. The aim of this paper is to compare the performance of the two different kinds of...
Background and objectives: Investigatingg the mortality in a population has been considered as one of the appropriate methods of health detection. Although, there are some problems such as lack of confidence in accuracy measurement and quality of data collection. Establishment of death registration systems and using international classification codes of diseases, and also mortality data integ...
A Fuzzy Mining Algorithm for Association-Rule Knowledge Discovery" (2005). ABSTRACT ABSTRASCT Due to increasing use of very large database and data warehouses, discovering useful knowledge from transactions is becoming an important research area. On the other hand, using fuzzy classification in data mining has been developed in recent years. Hong and Lee proposed a general learning method that ...
The problem of finding association rules from a dataset is to find all possible associations that hold among the items, given a minimum support value and a minimum confidence. This involves finding frequent sets first and then the association rules that hold within the items in the frequent sets. The problem of mining temporal association rules from temporal dataset is to find association rules...
The unprecedented growth of competition in the banking technology has raised the importance of retaining current customers and acquires new customers so that is important analyzing Customer behavior, which is base on bank databases. Analyzing bank databases for analyzing customer behavior is difficult since bank databases are multi-dimensional, comprised of monthly account records and daily t...
One of the most important data mining problems is mining association rules. In this paper we consider discovering association rules from large transaction databases. The problem of discovering association rules can be decomposed into two sub-problems: find large itemsets and generate association rules from large itemsets. The second sub-problem is easier one and the complexity of discovering as...
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