Validation on an enhanced dendrite cell algorithm using statistical analysis
Evaluating a novel or enhanced algorithm is compulsory in data mining studies in order to measure it has superior performance than its previous version. In practice, most of studies apply a straightforward approach for evaluation where appropriate performance metrics such as classification accuracy...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Insight - Indonesian Society for Knowledge and Human Development
2017
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/5245/ http://eprints.uthm.edu.my/5245/1/AJ%202017%20%28735%29.pdf |
| _version_ | 1848888502416048128 |
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| author | Mohamad Mohsin, Mohamad Farhan Hamdan, Abdul Razak Abu Bakar, Azuraliza Abd Wahab, Mohd Helmy |
| author_facet | Mohamad Mohsin, Mohamad Farhan Hamdan, Abdul Razak Abu Bakar, Azuraliza Abd Wahab, Mohd Helmy |
| author_sort | Mohamad Mohsin, Mohamad Farhan |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Evaluating a novel or enhanced algorithm is compulsory in data mining studies in order to measure it has superior performance than its previous version. In practice, most of studies apply a straightforward approach for evaluation where appropriate performance metrics such as classification accuracy is selected, computes the mean and its variance over several repetitive experiments, and then compares it with the base algorithm or other comparative approach. However, there are limitations using this approach because dataset from different domain tend to produce different error rate thus make their average meaningless as well as susceptible to the outlier. This study demonstrates the mechanism of evaluating an enhanced algorithm using performance metrics and validated it using statistical analysis. In this study, we evaluated the performance of the enhanced algorithm called dendrite cell algorithm using sensitivity, specificity, false positive rate, and accuracy and validated the result using parametric and non parametric statistical significant tests. From the evaluation, the new version of dendrite cell algorithm was statistically proven to have improvement with a significant difference compared to its previous versions in all performance metrics. |
| first_indexed | 2025-11-15T20:11:18Z |
| format | Article |
| id | uthm-5245 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:11:18Z |
| publishDate | 2017 |
| publisher | Insight - Indonesian Society for Knowledge and Human Development |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-52452022-01-06T07:49:40Z http://eprints.uthm.edu.my/5245/ Validation on an enhanced dendrite cell algorithm using statistical analysis Mohamad Mohsin, Mohamad Farhan Hamdan, Abdul Razak Abu Bakar, Azuraliza Abd Wahab, Mohd Helmy QA76 Computer software Evaluating a novel or enhanced algorithm is compulsory in data mining studies in order to measure it has superior performance than its previous version. In practice, most of studies apply a straightforward approach for evaluation where appropriate performance metrics such as classification accuracy is selected, computes the mean and its variance over several repetitive experiments, and then compares it with the base algorithm or other comparative approach. However, there are limitations using this approach because dataset from different domain tend to produce different error rate thus make their average meaningless as well as susceptible to the outlier. This study demonstrates the mechanism of evaluating an enhanced algorithm using performance metrics and validated it using statistical analysis. In this study, we evaluated the performance of the enhanced algorithm called dendrite cell algorithm using sensitivity, specificity, false positive rate, and accuracy and validated the result using parametric and non parametric statistical significant tests. From the evaluation, the new version of dendrite cell algorithm was statistically proven to have improvement with a significant difference compared to its previous versions in all performance metrics. Insight - Indonesian Society for Knowledge and Human Development 2017 Article PeerReviewed text en http://eprints.uthm.edu.my/5245/1/AJ%202017%20%28735%29.pdf Mohamad Mohsin, Mohamad Farhan and Hamdan, Abdul Razak and Abu Bakar, Azuraliza and Abd Wahab, Mohd Helmy (2017) Validation on an enhanced dendrite cell algorithm using statistical analysis. International Journal onAdvanced Science Engineering Information Technology, 7 (2). pp. 482-488. ISSN 2088-5334 https://dx.doi.org/10.18517/ijaseit.7.2.1743 |
| spellingShingle | QA76 Computer software Mohamad Mohsin, Mohamad Farhan Hamdan, Abdul Razak Abu Bakar, Azuraliza Abd Wahab, Mohd Helmy Validation on an enhanced dendrite cell algorithm using statistical analysis |
| title | Validation on an enhanced dendrite cell algorithm using statistical analysis |
| title_full | Validation on an enhanced dendrite cell algorithm using statistical analysis |
| title_fullStr | Validation on an enhanced dendrite cell algorithm using statistical analysis |
| title_full_unstemmed | Validation on an enhanced dendrite cell algorithm using statistical analysis |
| title_short | Validation on an enhanced dendrite cell algorithm using statistical analysis |
| title_sort | validation on an enhanced dendrite cell algorithm using statistical analysis |
| topic | QA76 Computer software |
| url | http://eprints.uthm.edu.my/5245/ http://eprints.uthm.edu.my/5245/ http://eprints.uthm.edu.my/5245/1/AJ%202017%20%28735%29.pdf |