Base on RFpS of Ensemble learning in Malware Family Classification
| Autor: | Wei-Chieh Chao, 趙偉傑 |
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| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 105 As we know some fundamental issues of data mining applications are much more critical and severe once it refers to malware analysis, and unfortunately, they are still not well-addressed. In this paper, the proposed a function, as well as uses supervised feature projection for redundant feature reduction and noise filtering. Combining Random Forest with SVM for named RFPS (Random Forest Predicated Svm), Method of reducing feature and fast classification. The results that the learning time about 4.5 times compared with the SVM, predicted speed increases by about 2.5 times, and the accuracy is about 20% to 98.4%. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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