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…into isic-classifier # Conflicts: # README.md
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я плохо поступил так как добавил .idea=( |
tanyapole
reviewed
Nov 10, 2019
| "source": [ | ||
| "def get_model_parameters_to_update(m:models.AlexNet) -> list:\n", | ||
| " params = []\n", | ||
| " for name, param in m.named_parameters():\n", |
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You can just use list(model.parameters()) for this
tanyapole
reviewed
Nov 11, 2019
.idea/.gitignore
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| @@ -0,0 +1,2 @@ | |||
| # Default ignored files | |||
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Please remove .idea files from git (you can use git rm -r --cached) and add this folder to .gitignore
tanyapole
requested changes
Nov 12, 2019
model_processing/validate_model.py
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| # trust result | ||
| for t in labels: | ||
| for idx, v in enumerate(t): | ||
| confusion_matrix[idx][v.item()][v.item()] += 1 |
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Why true labels are added to confusion matrix on par with predicted ones?
model_processing/validate_model.py
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| @staticmethod | ||
| def __calculate_f_measure(conf_matrix: torch.Tensor) -> float: | ||
| precision_w = 0 |
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f measure implementation is unclear to me. could you improve readability or explain it to me? which option did you choose https://scikit-learn.org/stable/modules/model_evaluation.html#from-binary-to-multiclass-and-multilabel?
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я сделал классификатор, думаю стоит обсудить его лично