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in function update_sample_space_model in case "if memory is full", I got confused about the prior weights renormalization step. why the loop is controlled by i < prior_weights_[i] instead of i < prior_weights_.size().
I cant see the meaning of the former one. I am looking forward to your reply:)
The text was updated successfully, but these errors were encountered:
also there is a step to ensure that the sample with higher prior weight is assigned id1. I think here you need
prior_weights_[closest_exist_sample_pair.y] >prior_weights_[closest_exist_sample_pair.x] instead of prior_weights_[closest_exist_sample_pair.x] >prior_weights_[closest_exist_sample_pair.y]
in function update_sample_space_model in case "if memory is full", I got confused about the prior weights renormalization step. why the loop is controlled by i < prior_weights_[i] instead of i < prior_weights_.size().
I cant see the meaning of the former one. I am looking forward to your reply:)
The text was updated successfully, but these errors were encountered: