Improvement of ANN-BP by data pre-segregation using SOM
Artificial intelligence is used to predict the onset of diabetes based on data measured from Pima Indians. This research is comparing the results gained from using same artificial neural networks-back propagation (ANN-BP) engine for 2 differently prepared data. The first data set consists of the ent...
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my.uniten.dspace-296842023-12-28T15:30:46Z Improvement of ANN-BP by data pre-segregation using SOM Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmed S.K. 26326032700 24463418200 24448864400 35606640500 25926812900 Artificial intelligenc Diabetes Kohonen Self Organizing Maps Neural networks Pima Indians Artificial intelligence Backpropagation Data flow analysis Measurements Strength of materials 2-group Artificial intelligenc Artificial Neural Network Cross validation Data sets Kohonen self-organizing maps Self organizing maps Artificial intelligence is used to predict the onset of diabetes based on data measured from Pima Indians. This research is comparing the results gained from using same artificial neural networks-back propagation (ANN-BP) engine for 2 differently prepared data. The first data set consists of the entire data set which is cross validated, while the second dataset is segregated into 2 groups using Kohonen Self Organizing Maps (SOM) which are then cross validated. Splitting the files prior to implementing the cross validation improves the general accuracy of the ANN-BP whereby the positively predicted diabetes cases percentage increased from 72% to 99%. Meanwhile the prediction of the negative diabetic cases percentage increased from 80% to 97%. � 2009 IEEE. Final 2023-12-28T07:30:46Z 2023-12-28T07:30:46Z 2009 Conference paper 10.1109/CIMSA.2009.5069941 2-s2.0-77950851517 https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950851517&doi=10.1109%2fCIMSA.2009.5069941&partnerID=40&md5=b72ae9d5978d4c50b73b905334598f96 https://irepository.uniten.edu.my/handle/123456789/29684 5069941 175 178 Scopus |
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Artificial intelligenc Diabetes Kohonen Self Organizing Maps Neural networks Pima Indians Artificial intelligence Backpropagation Data flow analysis Measurements Strength of materials 2-group Artificial intelligenc Artificial Neural Network Cross validation Data sets Kohonen self-organizing maps Self organizing maps |
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Artificial intelligenc Diabetes Kohonen Self Organizing Maps Neural networks Pima Indians Artificial intelligence Backpropagation Data flow analysis Measurements Strength of materials 2-group Artificial intelligenc Artificial Neural Network Cross validation Data sets Kohonen self-organizing maps Self organizing maps Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmed S.K. Improvement of ANN-BP by data pre-segregation using SOM |
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Artificial intelligence is used to predict the onset of diabetes based on data measured from Pima Indians. This research is comparing the results gained from using same artificial neural networks-back propagation (ANN-BP) engine for 2 differently prepared data. The first data set consists of the entire data set which is cross validated, while the second dataset is segregated into 2 groups using Kohonen Self Organizing Maps (SOM) which are then cross validated. Splitting the files prior to implementing the cross validation improves the general accuracy of the ANN-BP whereby the positively predicted diabetes cases percentage increased from 72% to 99%. Meanwhile the prediction of the negative diabetic cases percentage increased from 80% to 97%. � 2009 IEEE. |
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26326032700 |
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26326032700 Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmed S.K. |
| format |
Conference paper |
| author |
Weng L.Y. Omar J.B. Siah Y.K. Abidin I.B.Z. Ahmed S.K. |
| author_sort |
Weng L.Y. |
| title |
Improvement of ANN-BP by data pre-segregation using SOM |
| title_short |
Improvement of ANN-BP by data pre-segregation using SOM |
| title_full |
Improvement of ANN-BP by data pre-segregation using SOM |
| title_fullStr |
Improvement of ANN-BP by data pre-segregation using SOM |
| title_full_unstemmed |
Improvement of ANN-BP by data pre-segregation using SOM |
| title_sort |
improvement of ann-bp by data pre-segregation using som |
| publishDate |
2023 |
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1806427636395671552 |
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13.222552 |