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Machine learning Tensorflow与'；正阈值0.500000平均值'；？_Machine Learning_Tensorflow - Fatal编程技术网
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Machine learning Tensorflow与'；正阈值0.500000平均值'；？

machine-learning tensorflow

Machine learning Tensorflow与'；正阈值0.500000平均值'；？,machine-learning,tensorflow,Machine Learning,Tensorflow,Tensorflow发布了一系列统计数据： accuracy: 0.915224 accuracy/baseline_target_mean: 0.220896 accuracy/threshold_0.500000_mean: 0.915224 auc: 0.937926 global_step: 200 labels/actual_target_mean: 0.220896 labels/prediction_mean: 0.203677 loss: 0.247065 precision/p

Tensorflow发布了一系列统计数据：

accuracy: 0.915224
accuracy/baseline_target_mean: 0.220896
accuracy/threshold_0.500000_mean: 0.915224
auc: 0.937926
global_step: 200
labels/actual_target_mean: 0.220896
labels/prediction_mean: 0.203677
loss: 0.247065
precision/positive_threshold_0.500000_mean: 0.991379
recall/positive_threshold_0.500000_mean: 0.621622

baseline\u target\u是什么意思（精确后）和
positive\u threshold\u 0.500000\u是什么意思（回忆和精确后）？
既然你得到了这些统计数据，我假设你在做二元分类


baseline\u target\u mean
是数据中类标签的平均值，即在本例中，假设类标签为0和1，约22%的测试示例属于类1，其余示例属于类0。类标签可以是任意数字，因此解释取决于您的数据，我所描述的只是一种可能性，因为我不知道您使用的数据


positive_threshold_0.500000_mean
仅表示预测值高于阈值0.5的示例被视为正示例，而低于阈值0.5的示例被视为负示例