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License: Apache License 2.0
Coarse-to-Fine Curriculum Learning
License: Apache License 2.0
Hello!
In the file hierarchy_computation.py, I noticed that the code calculates the distance matrix (for affinity clustering) from the confusion matrix of a trained model.
However, in the paper, you state that there's a better way to calculate this distance which is calculating the cosine similarities between the columns of the predictor of a trained model.
Can your release the function that does this?
Hello.
I like your paper in which the new idea of curriculum learning was proposed.
But I must ask you a question.
Which did you get the confusion matrix from, training data or test data?
I think that getting the confusion matrix from test data is a kind of data leakage.
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