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This question relates specifically to the CvDTree decision tree class, but also to CvStatModel in general:

Is there a way to append additional training data to a model after the initial call to train() has been made?

According to the documentation, CvStatModel::clear() is generally called by the train() method. If this is the case, what is the most efficient strategy for updating the model with additional training examples? Does the model need to be retrained from scratch?

Thanks!

This question relates specifically to the CvDTree decision tree class, but also to CvStatModel in general:

Is there a way to append additional training data to a model after the initial call to train() has been made?

According to the documentation, CvStatModel::clear() is generally called by the train() method. If this is the case, what is the most efficient strategy for updating the model with additional training examples? Does the model need to be retrained from scratch?

Thanks!