Asymmetric cost loss function false negative cost 0
Defines a custom loss function in TensorFlow/Keras where predicting 1 as 0 (False Negative) has zero cost, while predicting 0 as 1 (False Positive) has a cost of 1.From its SKILL.md
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Asymmetric Cost Loss Function (False Negative Cost = 0)
Defines a custom loss function in TensorFlow/Keras where predicting 1 as 0 (False Negative) has zero cost, while predicting 0 as 1 (False Positive) has a cost of 1.
Prompt
Define a custom loss function in TensorFlow/Keras. The loss function must implement the logic where the cost of False Negatives (predicting 1 as 0) is 0. The cost of False Positives (predicting 0 as 1) is 1. Ensure type casting to float32 to avoid type mismatch errors.
Triggers
- 自定义一个评估标准，把1预测成0不算错
- 自定义loss函数
- 把1预测成0不算错
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