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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhang Huaizhong Hamprecht, F. Amann, A. |
| Copyright Year | 2005 |
| Description | Author affiliation: Sch. of Math. & Comput. Sci., Nanjing Normal Univ. (Zhang Huaizhong) |
| Abstract | Volatile organic compounds (VOCs) play an important role in diagnosis and therapy of various diseases. We compare several main classifiers for data classification and point out the advantages of randomForests on supervising learning. So, in this project, we take the randomForests approach to analyze and appraise the VOCs data originally coming from the medical test. According to actual situation, combining the unsupervising and supervising methods, the important components and outliers are given. The evaluation for the classifying results has been acquired due to the cross-validation sampling methods |
| Starting Page | 5 |
| Ending Page | 607 |
| File Size | 246915 |
| Page Count | 603 |
| File Format | |
| ISBN | 0769524869 |
| DOI | 10.1109/HPCASIA.2005.85 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-11-30 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Data analysis Medical treatment Diseases Medical diagnostic imaging Decision theory Volatile organic compounds Humans Gas detectors Pattern analysis Mathematics |
| Content Type | Text |
| Resource Type | Article |
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