نتایج جستجو برای: data mining association rules k means algorithm a priori algorithm
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Data envelopment analysis (DEA) is a relatively new data oriented approach to evaluate performance of a set of peer entities called decision-making units (DMUs) that convert multiple inputs into multiple outputs. Within a relative limited period, DEA has been converted into a strong quantitative and analytical tool to measure and evaluate performance. In an article written by Toloo et al. (2009...
Clustering is an important part of data mining. It can immensely simplify data complexity and helps discover the underlying patterns and knowledge from massive quantities data points. The popular efficient clustering algorithm k -means has been widely used in many fields. However, The k -means method also suffers from several drawbacks. It selects the initial cluster centers randomly that great...
abstract: although all university majors are prominent and the necessity of their presences is of no question, they might not have the same priority basis considering different resources and strategies that could be spotted for a country. this paper focuses on clustering and ranking university majors in iran. to do so, a model is presented to clarify the procedure. eight different criteria are ...
Clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. K-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. In recent years, several algorithms are provided based on evolutionary algorithms for cluster...
One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock market data to give individuals or institutions useful information about the market behavior for investment decisions. The enormous amount of valuable data generated by the stock market has attracted researchers to explore this problem domain using different methodologies. This pa...
web usage mining (wum) is the automatic discovering of hidden informationof user access pattern from the web log data. frequent pattern discovery is one ofthe main techniques in wum that can be used to implement recommender systems,forecast user`s navigational behaviour, and personalize web sites. many algorithmshave been suggested on obtaining frequent user navigation patterns. this paperprese...
Association rule mining is a fundamental and vital functionality of data mining. Most of the existing real time transactional databases are multidimensional in nature. In this paper, a novel algorithm is proposed for mining hybrid-dimensional association rules which are very useful in business decision making. The proposed algorithm uses multi index structures to store necessary details like it...
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