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 |