- Category:
- matlab
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- File Size:
- 4kb
- Update:
- 2018-04-17
- Downloads:
- 1 Times
- Uploaded by:
- voriarty
Description: The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules:
If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.
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File list (Check if you may need any files):
| Filename | Size | Date |
|---|
| MAIN.m | 6316 | 2018-04-12
|
| RELIEF.m | 1517 | 2017-12-22
|
| reliefF.m | 5357 | 2018-04-07 |
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