Using the symmetrical Tau criterion for feature selection decision tree and neural network learning
The data collected for various domain purposes usually contains some features irrelevant tothe concept being learned. The presence of these features interferes with the learning mechanism and as a result the predicted models tend to be more complex and less accurate. It is important to employ an eff...
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| Format: | Conference Paper |
| Published: |
ACM
2006
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| Online Access: | http://hdl.handle.net/20.500.11937/31352 |