keras.backend.binary_crossentropy

keras.backend.binary_crossentropy是一种计算二进制交叉熵损失的函数。它是通过计算真实标签和预测标签之间的交叉熵来衡量模型的训练误差。在深度学习中，二进制交叉熵通常用于二分类问题，其中每个样本只有两个可能的标签。该函数是通过调用tf.keras.backend.binary_crossentropy()来实现的。具体来说，它计算了真实标签和预测标签之间的二进制交叉熵，然后取平均值。这个函数在训练模型时经常用作损失函数。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* *2* [tensorflow+keras杂话](https://blog.csdn.net/weixin_43858032/article/details/125129718)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
- *3* [Keras中损失函数binary_crossentropy和categorical_crossentropy产生不同结果的分析](https://blog.csdn.net/qq_35599937/article/details/105608354)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_2"}}] [.reference_item style="max-width: 50%"]
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