Comparing performances of neural network models built through transformed and original data
Data transformation (normalization) is a method used in data preprocessing to scale the range of values in the data within a uniform scale to improve the quality of the data; as a result, the prediction accuracy is improved. However, some scholars have questioned the efficacy of data normalizati...
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| Language: | English English |
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2015
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| Online Access: | http://irep.iium.edu.my/44526/ http://irep.iium.edu.my/44526/ http://irep.iium.edu.my/44526/1/I4CT.pdf http://irep.iium.edu.my/44526/4/44526_Comparing%20performances%20of%20neural_Scopus.pdf |
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iium-445262017-09-21T03:37:27Z http://irep.iium.edu.my/44526/ Comparing performances of neural network models built through transformed and original data Abubakar, Adamu Haruna, Chiroma Abdulkareem, Sameem QA75 Electronic computers. Computer science Data transformation (normalization) is a method used in data preprocessing to scale the range of values in the data within a uniform scale to improve the quality of the data; as a result, the prediction accuracy is improved. However, some scholars have questioned the efficacy of data normalization, arguing that it can destroy the structure in the original (raw) data. To address these arguments, we compared the prediction performances of the two methods in the domain of crude oil prices due to its global significance. It was found that the multilayer perceptron neural network model that was built using normalized data significantly outperformed the multilayer perceptron neural network that was built using raw data. The number of iterations and the computation time for both of the methods were statistically equal as well as for the regression. In view of the arguments in the literature about data standardization, the results of this research could allow researchers in the domain of crude oil price prediction to choose the best opinion. 2015-08-30 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/44526/1/I4CT.pdf application/pdf en http://irep.iium.edu.my/44526/4/44526_Comparing%20performances%20of%20neural_Scopus.pdf Abubakar, Adamu and Haruna, Chiroma and Abdulkareem, Sameem (2015) Comparing performances of neural network models built through transformed and original data. In: International Conference on Computer, Communications, and Control Technology (I4CT), 2015, 21-23 April 2015, Kuching. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7194237&punumber%3D7194237%26filter%3DAND%28p_IS_Number%3A7219513%29%26pageNumber%3D3&pageNumber=4 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
International Islamic University Malaysia |
| building |
IIUM Repository |
| collection |
Online Access |
| language |
English English |
| topic |
QA75 Electronic computers. Computer science |
| spellingShingle |
QA75 Electronic computers. Computer science Abubakar, Adamu Haruna, Chiroma Abdulkareem, Sameem Comparing performances of neural network models built through transformed and original data |
| description |
Data transformation (normalization) is a method
used in data preprocessing to scale the range of values in the data
within a uniform scale to improve the quality of the data; as a
result, the prediction accuracy is improved. However, some
scholars have questioned the efficacy of data normalization,
arguing that it can destroy the structure in the original (raw)
data. To address these arguments, we compared the prediction
performances of the two methods in the domain of crude oil
prices due to its global significance. It was found that the
multilayer perceptron neural network model that was built using
normalized data significantly outperformed the multilayer
perceptron neural network that was built using raw data. The
number of iterations and the computation time for both of the
methods were statistically equal as well as for the regression. In
view of the arguments in the literature about data
standardization, the results of this research could allow
researchers in the domain of crude oil price prediction to choose
the best opinion. |
| format |
Conference or Workshop Item |
| author |
Abubakar, Adamu Haruna, Chiroma Abdulkareem, Sameem |
| author_facet |
Abubakar, Adamu Haruna, Chiroma Abdulkareem, Sameem |
| author_sort |
Abubakar, Adamu |
| title |
Comparing performances of neural network models
built through transformed and original data |
| title_short |
Comparing performances of neural network models
built through transformed and original data |
| title_full |
Comparing performances of neural network models
built through transformed and original data |
| title_fullStr |
Comparing performances of neural network models
built through transformed and original data |
| title_full_unstemmed |
Comparing performances of neural network models
built through transformed and original data |
| title_sort |
comparing performances of neural network models
built through transformed and original data |
| publishDate |
2015 |
| url |
http://irep.iium.edu.my/44526/ http://irep.iium.edu.my/44526/ http://irep.iium.edu.my/44526/1/I4CT.pdf http://irep.iium.edu.my/44526/4/44526_Comparing%20performances%20of%20neural_Scopus.pdf |
| first_indexed |
2023-09-18T21:03:18Z |
| last_indexed |
2023-09-18T21:03:18Z |
| _version_ |
1777410766940405760 |