Random sample consensus: Difference between revisions

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The idea is to continuously randomly sample a subset of your data.<br>
The idea is to continuously randomly sample a subset of your data.<br>
For each subset, you build a model and do cross-validation until you find a model with sufficiently small error.
For each subset, you build a model and do cross-validation until you find a model with sufficiently small error.
You quit after <math>k</math> iterations or once your model has sufficiently low error.


This is commonly used when you have a lot of points and building a model is worse than <math>O(n)</math>.<br>
This is commonly used when you have a lot of points and building a model is worse than <math>O(n)</math>.<br>