Careful evaluation of the classifier model is important so that we can truly understand the capabilities and performance of a Tc predicting model. Particularly important to us is the ability for the m
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Visualizing the counts of materials in the training and evaluation dataset by their Tc. First bin is non-superconductors, the rest are ranges of 20 K increments.
Not a very robust report yet. We're not through all the data points and these results come from a few different models (trained with more data as it came available)
Evaluating the validation set (1155 samples) on the trained CatBoost model to predict Tc.