| from sklearn.metrics import ( | |
| ConfusionMatrixDisplay, | |
| confusion_matrix, | |
| accuracy_score, | |
| f1_score | |
| ) | |
| import tempfile | |
| from pathlib import Path | |
| from sklearn.datasets import load_iris | |
| from sklearn.linear_model import LogisticRegression | |
| from skops import card | |
| X, y = load_iris(return_X_y=True) | |
| model = LogisticRegression(solver="liblinear", random_state=0).fit(X, y) | |
| model_card = card.Card(model) | |
| model_card.metadata.license = "mit" | |
| y_pred = model.predict(X) | |
| model_card.add_metrics(**{ | |
| "accuracy": accuracy_score(y, y_pred), | |
| "f1 score": f1_score(y, y_pred, average="micro"), | |
| }) | |
| model_card.add_plot(confusion_matrix="confusion_matrix.png") | |
| model_card.save("README2.md") |