A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big Data
One of the most common tasks nowadays in big data environments is the need to classify large amounts of data. There are numerous classification models designed to perform best in different environments and datasets, each with its advantages and disadvantages. However, when dealing with big data, the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Computation |
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| Online Access: | https://www.mdpi.com/2079-3197/8/3/80 |
| _version_ | 1827706502129909760 |
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| author | Christos Kalyvas Manolis Maragoudakis |
| author_facet | Christos Kalyvas Manolis Maragoudakis |
| author_sort | Christos Kalyvas |
| collection | DOAJ |
| description | One of the most common tasks nowadays in big data environments is the need to classify large amounts of data. There are numerous classification models designed to perform best in different environments and datasets, each with its advantages and disadvantages. However, when dealing with big data, their performance is significantly degraded because they are not designed—or even capable—of handling very large datasets. The current approach is based on a novel proposal of exploiting the dynamics of skyline queries to efficiently identify the decision boundary and classify big data. A comparison against the popular k-nearest neighbor (k-NN), support vector machines (SVM) and naïve Bayes classification algorithms shows that the proposed method is faster than the k-NN and the SVM. The novelty of this method is based on the fact that only a small number of computations are needed in order to make a prediction, while its full potential is revealed in very large datasets. |
| first_indexed | 2024-03-10T16:26:13Z |
| format | Article |
| id | doaj.art-2eb63f36ecea44958dcea251dbe65306 |
| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-03-10T16:26:13Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-2eb63f36ecea44958dcea251dbe653062023-11-20T13:10:17ZengMDPI AGComputation2079-31972020-09-01838010.3390/computation8030080A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big DataChristos Kalyvas0Manolis Maragoudakis1Department of Information and Communication Systems Engineering, University of the Aegean, 83200 Samos, GreeceDepartment of Informatics, Ionian University, 49100 Corfu, GreeceOne of the most common tasks nowadays in big data environments is the need to classify large amounts of data. There are numerous classification models designed to perform best in different environments and datasets, each with its advantages and disadvantages. However, when dealing with big data, their performance is significantly degraded because they are not designed—or even capable—of handling very large datasets. The current approach is based on a novel proposal of exploiting the dynamics of skyline queries to efficiently identify the decision boundary and classify big data. A comparison against the popular k-nearest neighbor (k-NN), support vector machines (SVM) and naïve Bayes classification algorithms shows that the proposed method is faster than the k-NN and the SVM. The novelty of this method is based on the fact that only a small number of computations are needed in order to make a prediction, while its full potential is revealed in very large datasets.https://www.mdpi.com/2079-3197/8/3/80classificationskylinebig datadecision boundary |
| spellingShingle | Christos Kalyvas Manolis Maragoudakis A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big Data Computation classification skyline big data decision boundary |
| title | A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big Data |
| title_full | A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big Data |
| title_fullStr | A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big Data |
| title_full_unstemmed | A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big Data |
| title_short | A Skyline-Based Decision Boundary Estimation Method for Binominal Classification in Big Data |
| title_sort | skyline based decision boundary estimation method for binominal classification in big data |
| topic | classification skyline big data decision boundary |
| url | https://www.mdpi.com/2079-3197/8/3/80 |
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