A comparative study of linear and nonlinear regression models for outlier detection
Artificial Neural Networks provide models for a large class of natural and artificial phenomena that are difficult to handle using classical parametric techniques. They offer a potential solution to fit all the data, including any outliers, instead of removing them. This paper compares the predictiv...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-319-51281-5_32 https://doi.org/10.1007/978-3-319-51281-5_32 |