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Online-Purchasing Behavior Forecasting with a Firefly Algorithm-based SVM Model Considering Shopping Cart Use

Ling Tang, Anying Wang, Zhenjing Xu, Jian Li
2017 Eurasia Journal of Mathematics, Science and Technology Education  
(AI) technique of support vector machine (SVM) is employed for classification forecasting and further extended by introducing the promising AI optimization tool of firefly algorithm (FA), to solve the  ...  Due to the complexity of the e-commerce system, a hybrid model for onlinepurchasing behavior forecasting is developed to predict whether or not a customer makes a purchase during the next visit to the  ...  ACKNOWLEDGEMENTS This work was supported by grants from the National Natural Science Foundation of China (NSFC Nos. 71433001, 71301006, 71571010, and 71622011), the National Program for Support of Top  ... 
doi:10.12973/ejmste/77906 fatcat:lpkdcwrfrfclfjueirhwbhwcaq

Complexity-based program phase analysis and classification

Chang-Burm Cho, Tao Li
2006 Proceedings of the 15th international conference on Parallel architectures and compilation techniques - PACT '06  
Modeling and analysis of program behavior are at the foundation of computer system design and optimization.  ...  We propose to apply wavelet-based multiresolution analysis and data clustering to classify program execution into phases that exhibit similar degree of complexity.  ...  For this reason, there is a growing interest in studying program phase behavior.  ... 
doi:10.1145/1152154.1152173 dblp:conf/IEEEpact/ChoL06 fatcat:esymsmii7jfbnl2xzkvb5qc2q4

Handling class imbalance in customer behavior prediction

Nengbao Liu, Wei Lee Woon, Zeyar Aung, Afshin Afshari
2014 2014 International Conference on Collaboration Technologies and Systems (CTS)  
Using a more appropriate evaluation metric (AUC), we investigated the increase of performance for under-sampling and two machine learning algorithms (weight Random Forests and RUSBoost) against a benchmark  ...  Weighted Random Forests, as a costsensitive learner, only improves the performance of appetency classification problem out of three classification problems.  ...  The rest of the report is organized as follows: in section II-A, we give a general description of the dataset used in this study and some data preprocessing techniques.  ... 
doi:10.1109/cts.2014.6867549 dblp:conf/cts/LiuWAA14 fatcat:siijogd6dzdxtem3l7fmscva4y

Using Wavelet Domain Workload Execution Characteristics to Improve Accuracy, Scalability and Robustness in Program Phase Analysis

Chang-Burm Cho, Tao Li
2007 2007 IEEE International Symposium on Performance Analysis of Systems & Software  
For long-running, complex and real-world workloads, a scalable phase analysis technique is essential to capture the manifested large-scale program behavior.  ...  Recently, there has been a growing interest in employing wavelets as a tool for phase analysis.  ...  For this reason, there is a growing interest in studying program phase behavior [2-4, 7, 10-19] . Several phase analysis techniques have been proposed [1, 7, 8, 13, 15] .  ... 
doi:10.1109/ispass.2007.363744 dblp:conf/ispass/ChoL07 fatcat:kqjxwmftczar3fnhxjzpz2ofra

Thread-level synthetic benchmarks for multicore systems

Alper Sen, Etem Deniz
2015 Microprocessors and microsystems  
One of the commonly used techniques to speedup early architectural exploration and performance evaluation of new hardware architectures is to use synthetic benchmarks.  ...  This paper presents a novel automated thread-level synthetic benchmark generation framework with characterization and generation components.  ...  Acknowledgments This research was supported in part by Semiconductor Research Corporation under task 2082.001, Bogazici University Research Fund 7223, and the Turkish Academy of Sciences.  ... 
doi:10.1016/j.micpro.2015.07.010 fatcat:6v2g4sezvvaz7axluhvhfdalia

IFS-CoCo in the Landscape Contest: Description and Results [chapter]

Joaquín Derrac, Salvador García, Francisco Herrera
2010 Lecture Notes in Computer Science  
In this work, we describe the main features of IFS-CoCo, a coevolutionary method performing instance and feature selection for nearest neighbor classifiers.  ...  The results obtained show that our proposal is a very competitive approach in the domains considered, outperforming both the benchmark results of the contest and the nearest neighbor rule.  ...  Derrac holds a research scholarship from the University of Granada.  ... 
doi:10.1007/978-3-642-17711-8_6 fatcat:r3x4xymwhrbshdma4qi2y7x3la

Guest Editorial: Special Section on IEEE International Conference on Software Quality, Reliability, and Security (QRS) 2020

W. K. Chan, Mei Nagappan, Christof Budnik
2021 IEEE Transactions on Reliability  
excelled in a learning task could be due to the data quality problem and show that there is a strong correlation between the quality of the datasets and the performance of a machine learning technique  ...  They proposed a transfer-learning-based strategy for data quality enhancement, thereby allowing existing techniques to improve their performance.  ...  that excelled in a learning task could be due to the data quality problem and show that there is a strong correlation between the quality of the datasets and the performance of a machine learning technique  ... 
doi:10.1109/tr.2021.3083119 fatcat:f3oowdi5nfdedpm4aloxfqpx74

A hybrid method of genetic algorithm and support vector machine for intrusion detection

Mushtaq Talb Tally, Haleh Amintoosi
2021 International Journal of Power Electronics and Drive Systems (IJPEDS)  
This study aims to propose a hybrid method of Genetic Algorithm and Support Vector Machine.  ...  GA has been as a feature selection in order to select the best features, while SVM has been used as a classification method to categorize the behavior into normal and intrusion based on the selected features  ...  The data used in this study is NSL-KDD benchmark dataset.  ... 
doi:10.11591/ijece.v11i1.pp900-908 fatcat:ymqkwuaswjgtdnaisg7lmfycle

SSPCO Optimization Algorithm (See-See Partridge Chicks Optimization)

Rohollah Omidvar, Hamid Parvin, Farhad Rad
2015 2015 Fourteenth Mexican International Conference on Artificial Intelligence (MICAI)  
SSPCO optimization algorithm is a new optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge.  ...  In the present article, a chaotic SSPCO algorithm is utilized for clustering data on different benchmarks and datasets; moreover, clustering with artificial bee colony algorithm and particle mass 9 clustering  ...  Clustering of the 13 benchmark criteria is similar to and consistent with all algorithms, and the techniques are compared with SSPCO algorithm. 75% of the data for each data set is dedicated to education  ... 
doi:10.1109/micai.2015.22 dblp:conf/micai/OmidvarPR15 fatcat:go5inzy37jc7xbb7giei2uma24

Did they sense it coming? A pipelined approach for tsunami prediction based on aquatic behavior using ensemble clustering and fuzzy rule-based classification

Nikita Jain, Deepali Virmani, Ajith Abraham, Lorenzo Salas-Morera, Laura Garcia-Hernandez
2020 IEEE Access  
Therefore, we propose a sequenced (EC G F C ) approach for designing a TWS, based on Ensemble Clustering (EC G ) and Classification for categorizing anomalous behavior in response to seismic perturbations  ...  EC G uses an existing state-of-the-art method bagged with Gaussian mixture model to label the dynamically changing behavioral data.  ...  Recently, a contribution [24] which reviews the impact of machine learning techniques to model complex behavioral data has attracted attention.  ... 
doi:10.1109/access.2020.3022865 fatcat:b4ie33saczeylfiz5wp7junsxa

Hybrid Intrusion Detection Using Ensemble of Classification Methods

M. Govindarajan
2014 International Journal of Computer Network and Information Security  
A wide range of comparative experiments are conducted for real and benchmark data sets of intrusion detection.  ...  The feasibility and the benefits of the proposed approaches are demonstrated by the means of real and benchmark data sets of intrusion detection.  ...  ACKNOWLEDGMENT Author gratefully acknowledges the authorities of Annamalai University for the facilities offered and encouragement to carry out this work.  ... 
doi:10.5815/ijcnis.2014.02.07 fatcat:jeee2oxzt5emjkvx2czqyfz2sm

More Buildings Make More Generalizable Models—Benchmarking Prediction Methods on Open Electrical Meter Data

Clayton Miller
2019 Machine Learning and Knowledge Extraction  
An analysis of the generalizability of the models tested motivates the need for the application of future techniques to a board range of building types and behaviors.  ...  Prediction is a common machine learning (ML) technique used on building energy consumption data.  ...  However, these studies are problematic for use as a benchmarking data set for other researchers due to the lack of access to the exact models or data used.  ... 
doi:10.3390/make1030056 fatcat:cmoa7xfknve4jbyg3hhbnkqvwa

Reaching a consensus on access detection by a decision system

Cesar Guevara, Matilde Santos, Jose Antonio Martin, Victoria Lopez
2014 2014 IEEE International Conference on Progress in Informatics and Computing  
In order to validate the system, a scenario based on real data of the NSL-KDD99 dataset is used.  ...  Classification techniques based on Artificial Intelligence are computational tools that have been applied to detection of intrusions (IDS) with encouraging results.  ...  ACKNOWLEDGMENTS Authors would like to thank the reviewers for their helpful comments.  ... 
doi:10.1109/pic.2014.6972308 fatcat:2xdgufrfl5atxmrvl43huzt4gi

Improving direct mail targeting through customer response modeling

Kristof Coussement, Paul Harrigan, Dries F. Benoit
2015 Expert systems with applications  
Second, we run a predictive benchmarking study using the above classifiers on four real-life direct marketing datasets.  ...  The findings of the benchmark study show that data-mining algorithms (CHAID, CART and neural networks) perform well on this test bed, followed by simplistic statistical classifiers like logistic regression  ...  Logistic regression Logistic regression (LOG) is a well-known and industry-standard classification technique for predicting a dichotomous dependent variable such as respond/do not respond to a mailing  ... 
doi:10.1016/j.eswa.2015.06.054 fatcat:yu7bvw4rdfexllsrcwetixp5aa

Customer-Centric Decision Support

Stefan Lessmann, Stefan Voß
2010 Business & Information Systems Engineering  
The observed results provide strong evidence for the value of modern techniques and identify one approach which appears to be particularly well suited for solving customer-centric classification problems  ...  In particular, the domain of customer relationship management comprises a variety of respective applications, which involve estimating some aspects of customer behavior.  ...  Table 1 1 Classification methods of the benchmarking study Classifier Description Table 2 2 Characteristics of the datasets employed in the benchmarking study No. of cases No. of attributes A priori  ... 
doi:10.1007/s12599-010-0094-8 fatcat:ku6yftrmmveuhm6urngnqnmfji
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