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The key idea of GRAB is to adopt weighted frequent itemset mining for the most time-consuming step in the grafting algorithm, which is designed to solve largescale L 1 -RERM problems by an iterative approach ... We consider the class of linear predictors over all logical conjunctions of binary attributes, which we refer to as the class of combinatorial binary models (CBMs) in this paper. ... Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution ...doi:10.1007/s10618-019-00657-9 fatcat:yhj76nejxzcgte27lzybuqos4u
The key idea of GRAB is to reduce the loss minimization problem to the weighted frequent itemset mining, in which frequent patterns are efficiently computable. ... This paper introduces the combinatorial Boolean model (CBM), which is defined as the class of linear combinations of conjunctions of Boolean attributes. ... CONCLUSION In this paper we proposed GRAB that is an algorithm for learning combinatorial boolean models (CBM). e key idea of GRAB was to incorporate the techniques of frequent itemset mining with the ...arXiv:1711.02478v2 fatcat:52qegzbssngkvf3epu2qlz6vfy
It will examine for all records which are not at altogether used and wanted by the consumer. ... In this mission, the website is working to find the available frequent stuff using the procedure called APRIORI. ... Searching frequent itemset is not unimportant because of this one combinatorial blast. ...doi:10.17485/ijst/2017/v10i17/114477 fatcat:panxioy6dbgyxfgl4t2agoe3vu
We are grateful to all members of these committees for their time and efforts. ... In all three occasions, the Canadian Databases community served as backbone for the organizing and the programme committees. ... contents presented in this document would not have been available to the attendees of the VLDB conference without the contributions of Mike Godfrey (MG) and Dave Wortman (DW), who compiled similar guides for ...doi:10.1109/dsn.2006.75 dblp:conf/dsn/X06 fatcat:k4duddvbk5glboxkqxkkfsh4p4
We show that by using a simple bag-of-words model, univariate feature selection, 320 strongest features and a standard classifier, we reach user classification accuracy of ∼98%. ... Acknowledgements The authors wish to thank Airenas Vaiciunas from the Department of Applied Informatics at Vytautas Magnus University (Lithuania) for his useful comments about SLMs and also to Semantia ... Lab (www.semantialab.es) for supporting the logistic of this research. ...fatcat:5ab4ab7jybdpldte54cxglvcne
In the first part of study, the effects of UV and TiO 2 on two antibiotics using the UV-water flow system (UVWFS) were examined. ... In second part of the study, three (15, 42 and 80 cc/min) water flow rates were employed using UVWFS maintaining same UV and TiO 2 dose 0.1 g/l to ascertain the effect of water flow rate in the antibiotic ... The results emphasise that for adsorption from surfactant mixtures, it is necessary to take into account the changes in the CMC with changes in composition. ...doi:10.5539/mas.v3n2p0 fatcat:4bjvcqfu5jg7bbzxcjoq477gcy