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→Example: Simplified a sentence of RANSAC algorithm explanation. |
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# Select a random subset of the original data. Call this subset the ''hypothetical inliers''.
# A model is fitted to the set of hypothetical inliers.
# All other data are then tested against the fitted model. Those points that fit the estimated model well, according to some model-specific [[loss function]], are considered as a part of the ''consensus set''.
# The estimated model is reasonably good if sufficiently many points have been classified as part of the consensus set.
# Afterwards, the model may be improved by reestimating it using all members of the consensus set.
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