museotoolbox.ai.SequentialFeatureSelection.predict_images¶
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SequentialFeatureSelection.
predict_images
(in_image, out_image_prefix, in_image_mask=False, higher_confidence=False)[source]¶ Predict each best found features with SFFS.fit(X,y).
- Parameters
in_image (str.) – Path of the raster to predict.
out_image_prefix (str.) – Prefix of each raster to save. Will add in suffix the iteration number then .tif. E.g. outRasterPrefix = classification_, will give classification_0.tif for the first prediction.
in_image_mask (str or False, optional (default=False)) – Path to the image mask where 0 values are masked data.
higher_confidence (False or str. Default False.) – If str, same as outRasterPrefix.