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Data Mining and Data Visualization Using Self-Organizing Map (SOM)
| Content Provider | Semantic Scholar |
|---|---|
| Author | Khan, Ahmad Khan, Bin Jamil |
| Copyright Year | 2017 |
| Abstract | Data min ing and data visual izati ons are becoming essential parts in inform ation techno logy in recent e ra. Wi thout the existence of data minin g techno logy, big data can be near imposs ible to be ex tracted and have to be done manually. With the aid of data mining techn ology, now information can be gathered from data sets at much shorter time. The di scovery of data visua lizati ons a lso aid s in managing data into presen table fom) that can be understood by everyone. B ig dimensions can now be reduced to help data be more understandable . In this thesis, Kohonen se lf-organiz ing map(SOM) technique is di scussed and examined for data mining and data visualizations. SOM is a neural network technique that can performs data mining, data classificat ion and data visua lizati ons. SOM Too lbox was used on MATLAB. All steps in SOM are exp la ined in detail s from weight initi a lization until trai nin g is stopped . Graphical explanations of how SOM works are a lso used to help vi sua li ze SOM a lgorithm. Many methods of visualizations a re di splayed in the thesis. A ll methods are criti call y ana lysed. Few benchmark datasets are used as examples of the visua li zation techniques. Such examples are Iri s datasets and Wine data sets. The strength and weaknesses are I isted out in discuss ion section . |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://ir.unimas.my/id/eprint/20939/1/Data%20mining%20and%20data%20visualization%20using%20self-organizing...(24%20pgs).pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
