Compute “meta-features for a set of prototypes.
Parameters: | prototypes – Prototype data. |
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Returns: | Array of meta-features, with one row per prototype. |
Return type: | array of float |
Train a patch quality model.
Parameters: |
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Returns: | A trained model. |
Return type: | sklearn.base.RegressorMixin |
Learn patch models by meta-feature weighted k-Means clustering.
Weights are given by a feature quality prediction model using prototype “meta-features”.
Parameters: |
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Returns: | Learned patches. |
Return type: | array of float |