Hi, I built a classification model based on the hybrid structural model learned from a dataset with 6 features and ~40k records following the tutorial, Evaluated the model on the test set, and got 0 for precision and recall for class 1. I tried constructing the model with different parameters, but this won't seem to fix the issue and I keep getting 0 for precision and recall, even though the full dataset includes ~20% of class 1. What might be wrong here? I would appreciate any feedback or suggestions.
Contact Details
yhcho@umich.edu
Short description of the problem here.
Hi, I built a classification model based on the hybrid structural model learned from a dataset with 6 features and ~40k records following the tutorial, Evaluated the model on the test set, and got 0 for precision and recall for class 1. I tried constructing the model with different parameters, but this won't seem to fix the issue and I keep getting 0 for precision and recall, even though the full dataset includes ~20% of class 1. What might be wrong here? I would appreciate any feedback or suggestions.
{'Target_0': {'precision': 0.8104828298476633, 'recall': 1.0, 'f1-score': 0.8953223046206502, 'support': 3139.0}, 'Target_1': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 734.0}, 'accuracy': 0.8104828298476633, 'macro avg': {'precision': 0.40524141492383164, 'recall': 0.5, 'f1-score': 0.4476611523103251, 'support': 3873.0}, 'weighted avg': {'precision': 0.6568824174778763, 'recall': 0.8104828298476633, 'f1-score': 0.7256433550746763, 'support': 3873.0}}
CausalNex Version
0.12.1
Python Version
3.9.18
Relevant code snippet
Relevant log output
No response
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