Local Binary Signed Pressure Force Function Based Variation Segmentation Model
Volume 9 Issue 1 2015
Download| Author(s): | Adnan Alam khan, Shariq Ahmed |
|---|---|
| Abstract | The aim of this study is to highlight significance of data mining in health science. For this study lungs patient samples are collected to get the desired results. Data set of 350 patients is used in Weka and R for analysis and forecasting. In this research, we will highlight effective and common methods for classification using decision tree algorithm within data mining. There is also an introduction of two most common tools Rattle R and Weka. In the end we have presented a comparison between the both tools on 350 real dataset measuring the accuracy of tools. Further included to both have the capacity to produce tree demonstrate in less time. Some way or another Rattle is quicker than Weka that may be because of the inner structure of Rattle R which is sorted out in sections in memory. In this paper we can see plainly that Weka in term of precision is superior to anything Rattle R. In future, we can actualize this model on bigger up and coming information set of patient to foresee proper treatment routines. |
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| Year | 2015 |
| Volume | 9 |
| Issue | 1 |
| Type | Research paper, manuscript, article |
| Journal Name | Journal of Information & Communication Technology | Publisher Name | ILMA University | Jel Classification | - | DOI | - | ISSN no (E, Electronic) | 2075-7239 | ISSN no (P, Print) | 2415-0169 | Country | Pakistan | City | Karachi | Institution Type | University | Journal Type | Open Access | Manuscript Processing | Blind Peer Reviewed | Format | Paper Link | https://jict.ilmauniversity.edu.pk/journal/jict/9.1/4.pdf | Page | 33-40 |