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Robust refers to the internal mechanism or nature of a system that prevents it from being affected by disturbances such as stress or environmental changes (Wikipedia)
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- Sometimes, large noise can cause significant changes in the output.
- As a tendency, the model learns from data with less noise first.
- Two learners can become more robust to noise by sharing information with each other.
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- Difficult classifications are rejected and left to humans, especially for critical domains such as medical and financial where mistakes are not acceptable.
- Approach 1: Reject objects with low confidence as they are (with limitations).
- Approach 2: Train a classifier and a rejector separately, and use the rejector for rejection.
- This approach works well for binary problem, but not for more complex problems.
Class Classification
Machine Learning
(Source: Information Science Expert)