asymmetric-cost-loss-function-false-negative-cost-0

id	5839394e-59fb-4edf-8d15-b11a4cb09436
name	Asymmetric Cost Loss Function (False Negative Cost = 0)
description	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.
version	0.1.0
tags	["tensorflow","keras","loss function","asymmetric cost","imbalanced data","machine learning"]
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"]

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