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Mining The Successful Binary Combinations: Methodology and A Simple Case Study
[article]
2010
arXiv
pre-print
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, and parameter combination leading to a product success. ...
The importance of finding the characteristics leading to either a success or a failure is one of the driving forces of data mining. ...
Case Study The purpose of the case study is to illustrate the stages of the proposed methodology. Due to the obvious space constraints, a small case study is chosen. ...
arXiv:1002.1159v1
fatcat:psdzlcl3t5b5bekkiul4s4wqsy
Combined Survey Sampling Inference
2004
Technometrics
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BOOK REVIEWS All chapters begin with nice overviews and conclude with sections devoted to "Further Reading." ...
Competitors for this particular book are limited to books on logistic regression or generalized linear modeling, such as that by Myers, Montgomery, and Vining (2002) , which was reviewed for Technometrics ...
A case in point is the lowess, or loess, methodology developed by Bill Cleveland and co-workers at Lucent, made available in S-PLUS and SAS. ...
doi:10.1198/tech.2004.s750
fatcat:qpilh36ovfgahpfia2l4hevl3a
Developing Decision Tree based Models in Combination with Filter Feature Selection Methods for Direct Marketing
2020
International Journal of Advanced Computer Science and Applications
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Data was taken from a Portuguese bank direct marketing campaign. A filter-based Feature selection is applied in the study to improve the performance of the classification. ...
Thus special Data Mining techniques are needed in order to analyze these data, predict campaigns efficiency and give decision makers indications regarding the main marketing features affecting the marketing ...
This study aims to use a simple and comprehensive data mining model which is easy to be understood by users with little or no technical background, especially that decision makers in this case are usually ...
doi:10.14569/ijacsa.2020.0110180
fatcat:z4klurvlzzegrgdbbhx76xdcyi
Combining complex networks and data mining: Why and how
2016
Physics reports
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2016 pre-print arXiv:1604.08816v1 fatcat:mmozaxqqb5du3ag6abyonwfmd4Other Versions
In the face of that, a surprisingly low number of researchers turn out to resort to both methodologies. ...
A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented. ...
list (and, for that, we deeply apologise), which equally inspired our efforts, and opened up our minds in a way that contributed, eventually and substantially, to the realisation of the present survey ...
doi:10.1016/j.physrep.2016.04.005
fatcat:dp33n23k7vhdfg7nm6lfo57adu
Combining Bagging And Additive Regression
2007
Zenodo
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Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. ...
We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy. ...
We performed a comparison with simple bagging and boosting ensembles on standard benchmark datasets and we took better accuracy in most cases. ...
doi:10.5281/zenodo.1062831
fatcat:qxkjlujnffa3pjrjksywgw57sy
Combining complex networks and data mining: why and how
[article]
2016
bioRxiv
pre-print
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In the face of that, a surprisingly low number of researchers turn out to resort to both methodologies. ...
A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented. ...
Nowadays, this distinction is almost lost, and "data mining" is used to refer to the overall process performed by combining methodologies and techniques from different fields, such as statistics, databases ...
doi:10.1101/054064
fatcat:ncnw5vdvnfawxiq52vyzqtziuu
Improved multiclass feature selection via list combination
2017
Expert systems with applications
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When using SVM-RFE on a multiclass classification problem, the usual strategy is to decompose it into a series of binary ones, and to generate an importance statistics for each feature on each binary problem ...
These importances are then averaged over the set of binary problems to synthesize a single value for feature ranking. In some cases, however, this procedure can lead to poor selection. ...
In both cases, we created the corresponding binary problems and 248 produced a ranking of features for each of them. ...
doi:10.1016/j.eswa.2017.06.043
fatcat:s6jiw6e6mneahextwpyvds3t4a
Takeover prediction using forecast combinations
2013
International Journal of Forecasting
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Forecasts from several non-linear forecasting models, such as logistic and neural network models and a combination of them, are used to explore the methodology that better reduces the out-of-sample misclassification ...
First, the forecast combination method outperforms that of the single models and should be used to improve the prediction accuracy of takeover targets. ...
Nonetheless, the combination of probability forecasts of a binary variable defined on the [0, 1] interval appeared later when Kamstra and Kennedy (1998) introduced a method to combine log-odds ratios ...
doi:10.1016/j.ijforecast.2013.01.008
fatcat:zofwyg6hanci3estvzxx4sarea
On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems
2015
Expert systems with applications
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The goodness of our methodology is supported by means of a complete experimental study, in which we contrast the quality of our results versus the state-of-the-art of Genetic Fuzzy Systems for intrusion ...
a "normal activity" and the different attack types. ...
The authors therefore, acknowledge technical and financial support of KAU. ...
doi:10.1016/j.eswa.2014.08.002
fatcat:i2lg4yaayzc5fhjiof6uyog7em
Hybrid stacked ensemble combined with genetic algorithms for Prediction of Diabetes
[article]
2021
arXiv
pre-print
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In this study, the Ensemble training methodology based on genetic algorithms are used to accurately diagnose and predict the outcomes of diabetes mellitus. ...
Diabetes is currently one of the most common, dangerous, and costly diseases in the world that is caused by an increase in blood sugar or a decrease in insulin in the body. ...
Acknowledgment We are thankful to our colleagues who provided expertise that greatly assisted the research.
Source of funding
١٠ All the funding of this study was provided by the authors. ...
arXiv:2103.08186v1
fatcat:ngn3ty5shbhxvomycmhstjqqd4
FLOSS 2013: a survey dataset about free software contributors: challenges for curating, sharing, and combining
2014
Proceedings of the 11th Working Conference on Mining Software Repositories - MSR 2014
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We describe as well the possibilities and challenges of using private information from the survey when linked with other, publicly available data sources. ...
In this data paper we describe a data set obtained by means of performing an on-line survey to over 2,000 Free/Libre/Open Source Software (FLOSS) contributors. ...
In the meantime, we will combine the data internally, as we have done in the case study shown next. ...
doi:10.1145/2597073.2597129
dblp:conf/msr/RoblesRSVG14
fatcat:g3nmylskz5dyvlrzxc4g4kw5zm
Ontology Employment in Text Document Clustering combined with Grouping Algorithm
2013
International Journal of Applied Information Systems
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For the experiments the system has to use ontology that enables us to describe and organize this from heterogeneous sources, and to cluster about it. ...
Moreover, there are many of computer science and medical based subject related papers and journals cited on the Internet. ...
But this method only considers the times which the words appear, while ignoring other factors which may impact the word weighs. And also this method is only a binary weighting method. ...
doi:10.5120/ijais13-451026
fatcat:ndsgnkkodrbinc5iqru5njdw74
Matching Spatial Regions with Combinations of Interacting Gene Expression Patterns
[chapter]
2008
Communications in Computer and Information Science
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In this study, we construct a grammar to define spatial regions by combinations of these patterns. ...
The space of combinations is searched using an evolutionary algorithm with the objective of finding the best match to a given target pattern. ...
[2] study. This work has made use of the resources provided by the Edinburgh Compute and Data Faclity (ECDF) http://www.ecdf.ed.ac.uk/. ...
doi:10.1007/978-3-540-70600-7_26
fatcat:mh5xyfx34rcvjlx6vzwftuis5q
Combination of Topic Modelling and Decision Tree Classification for Tourist Destination Marketing
[chapter]
2020
Lecture Notes in Business Information Processing
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The proposed method combines topic modelling using Structured Topic Analysis with sentiment polarity, information on culture, and purchasing power of tourists for the development of a Decision Tree (DT ...
The patterns that emerged from the DT are expressed in terms of rules that highlight variable combinations leading to negative or positive sentiment. ...
These are described in turn along with the overall proposed methodology that combines them. ...
doi:10.1007/978-3-030-49165-9_9
fatcat:7xy3tf3tlvdgripfrw2jenzp34
Expert System Based on Multi-Stage Approach Combining Feature Selection with Machine Learning Techniques for Diagnosis of Thyroid Disease
2022
IJARCCE
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According to a study report published in the journal Lancet in February 2022 1 type 1 diabetes among people under the age of 25 accounted for at least 73.7% of the overall 16,300 diabetes fatalities in ...
The output findings were compared to those of previous research on the same dataset, and the proposed model was determined to be the most successful across all performance dimensions. 1. https://www.downtoearth.org.in ...
The flowchart and architectural design of the experimental design and model building is depicted in Figure 1 , Figure 2 and Figure 3 .
2.CHOICE OF DATA MINING MODELS This study investigated data-mining ...
doi:10.17148/ijarcce.2022.11341
fatcat:ewuy6f6om5a4hjhpwzviukiikq
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