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DC Field | Value | Language |
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dc.contributor.author | Mumtazimah Mohamad | - |
dc.date.accessioned | 2015-06-13T08:12:52Z | - |
dc.date.available | 2015-06-13T08:12:52Z | - |
dc.date.issued | 2014-07 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/3430 | - |
dc.description.abstract | Large datasets related tasks are a great challenge for applications that involve massive amounts of data with high dimensional spaces. hence have gained considerable attention in academic research. Due to its enormous size. the datasets poses a more complex problem especially in classification tasks where the datasets have different characteristics. Currently, most machine learning algorithms are able to deal with small to medium sizes of datasets with the use of single memory computer. However, classification of large datasets with the respective algorithms is impractical since it could reduce computer performance and is size-limited for a single processor with one memory. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Terengganu: Universiti Malaysia Terengganu | en_US |
dc.subject | QA 76.87 .M8 M3 2014 | en_US |
dc.subject | Mumtazimah Mohamad | en_US |
dc.subject | Neural networks -- Computer science | en_US |
dc.title | A framework of ensemble artificial neural networks model for classification of large datasets | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Pusat Pengajian Informatik dan Matematik Gunaan |
Files in This Item:
File | Description | Size | Format | |
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QA 76.87 .M8 M3 2014 Abstract.pdf | 7.9 MB | Adobe PDF | View/Open | |
QA 76.87 .M8 M3 2014 FullText.pdf Restricted Access | 274.25 MB | Adobe PDF | View/Open Request a copy |
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