Tensorflow Estimator评估指标精度和召回率

时间:2019-02-08 16:34:12

标签: python tensorflow tensorflow-estimator

我想知道为什么我的estimator.evaluate只给出---------------------------------------------------------------------------------------------------- Training for step = 0 Train Time (s): 71.8534505367279 Eval Metrics (Validation): {'accuracy': 0.98585105, 'average_loss': 0.03573704, 'loss': 4.5569196, 'global_step': 100} ---------------------------------------------------------------------------------------------------- ,但由于类极度不平衡而没用。

Recall

我确实看到其他人还有其他指标,例如Precision---------------------------------------------------------------------------------------------------- Training for step = 0 Train Time (s): 78.62789511680603 Eval Metrics (Train): {'accuracy': 0.84863335, 'accuracy_baseline': 0.5005, 'auc': 0.9279859, 'auc_precision_recall': 0.92819566, 'average_loss': 0.34581015, 'label/mean': 0.5005, 'loss': 44.145977, 'precision': 0.86890674, 'prediction/mean': 0.47957155, 'recall': 0.8215118, 'global_step': 100} Eval Metrics (Validation): {'accuracy': 0.8454, 'accuracy_baseline': 0.505, 'auc': 0.92413086, 'auc_precision_recall': 0.9200026, 'average_loss': 0.35258815, 'label/mean': 0.495, 'loss': 44.073517, 'precision': 0.8522351, 'prediction/mean': 0.48447067, 'recall': 0.8319192, 'global_step': 100} ---------------------------------------------------------------------------------------------------- 等。而没有添加任何评估挂钩e.g. here

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我从文档中找不到该怎么做,也许我错过了一些东西。感谢您的帮助!

最佳

0 个答案:

没有答案