Results 41 to 50 of about 391,967 (186)
Fuzzy Association Rule Mining [PDF]
Journal of Computer Science, 2015 The paper attempts to propose a fuzzy logic association algorithm to predict the risks involved in identifying diseases like breast cancer. Fuzzy logic algorithm is used to find association rules. The results of the study revealed that the prediction is better reliable than conventional methods.
A. Lekha, C. V. Srikrishna, Viji Vinod
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The Analysis of the Influencing Factors on the Problems of Bike-Sharing System in China
IEEE Access, 2019 Bike-sharing has experienced rapid growth in China since 2016. Notwithstanding the fast expansion, or possibly because it grew too fast, some bike-sharing companies have experienced setbacks and failure in 2018.
Shianghau Wu, Xuxiunan Lei
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, 2010 Coron is a domain and platform independent, multi-purposed data mining toolkit, which incorporates not only a rich collection of data mining algorithms, but also allows a number of auxiliary operations. To the best of our knowledge, a data mining toolkit
Kaytoue, Mehdi +4 more
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Socioeconomic inequality of cancer mortality in the United States: a spatial data mining approach
International Journal of Health Geographics, 2006 Background The objective of this study was to demonstrate the use of an association rule mining approach to discover associations between selected socioeconomic variables and the four most leading causes of cancer mortality in the United States.
Lam Nina SN, Vinnakota Srinivas
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, 2008 Tato bakalářská práce se zabývá dolováním asociačních pravidel. První část se věnuje vysvětlení technologie dolování dat a teorie, kterou je dobré znát pro seznámení se s asociační analýzou.
Šabatka, Ondřej
core
Incremental Fuzzy Association Rule Mining for Classification and Regression
IEEE Access, 2019 The aim of mining fuzzy association rules is to find both the association and the casual relationships between the itemsets. With the arrival of dynamic data, the fuzzy association rules should be updated in real time.
Ling Wang, Qian Ma, Jianyao Meng
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Granular association rules for multi-valued data
, 2013 Granular association rule is a new approach to reveal patterns hide in many-to-many relationships of relational databases. Different types of data such as nominal, numeric and multi-valued ones should be dealt with in the process of rule mining.
Min, Fan, Zhu, William
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Research on Mining Algorithm for Association Co-occurrence Rule of Moving Targets [PDF]
Jisuanji gongcheng, 2018 The current mobile target behavioral rules mostly focus on the single dimension of space or time,or the self-behavior of a single moving target.In order to find out the association co-occurrence rule of moving targets,based on the traditional trajectory ...
XIE Bin,ZHANG Kun,CAI Ying,JIANG Tongtong,MA Mengyue
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Spatial Data Preprocessing for Mining Spatial Association Rule with Conventional Association Mining Algorithms [PDF]
, 2007 The increasing usage of Geographical Information Systems (GIS) for various problems makes the volume of spatial data is growing fast. Spatial data mining is one of the several ways to find the new knowledge from data collection.
Mukhlash, Imam, Sitohang, Benhard
core
Text Classification Using Association Rules, Dependency Pruning and Hyperonymization
, 2014 We present new methods for pruning and enhancing item- sets for text classification via association rule mining. Pruning methods are based on dependency syntax and enhancing methods are based on replacing words by their hyperonyms of various orders.
Haralambous, Yannis, Lenca, Philippe
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