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使用提供的评测数据,得到的评测结果有问题。
eval_accuracy = 0.86040765 eval_f1 = 0.9527646 eval_loss = 0.5360181 eval_precision = 0.9510234 eval_recall = 0.95451
在precision和recall均在0.95时,accuracy理论上也在0.95左右 作者给出的评测代码对于多分类情况同样也是有问题的。 另外,因为tensorflow的tf.metrics实现的问题,在评测数据量较大时计算也会有问题。
The text was updated successfully, but these errors were encountered:
如果能有评测结果的文件(格式可以是:正确标签\t预测标签\t正文),使用sklearn的metrics包也可以得到正确结果。 发现output目录下有eval.tf_record文件,估计只是方便后续处理生成的中间结果文件 有没有方法可以输出最终的评测结果文件呢?
eval.tf_record
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precision = TP / (TP + FP) recall = TP / (TP + FN) accuracy = (TP + TN) / (TP + FP + TN + FN)
在precision和recall均在0.95时,accuracy理论上也在0.95左右
这个是怎么算出来的?
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使用提供的评测数据,得到的评测结果有问题。
在precision和recall均在0.95时,accuracy理论上也在0.95左右
作者给出的评测代码对于多分类情况同样也是有问题的。
另外,因为tensorflow的tf.metrics实现的问题,在评测数据量较大时计算也会有问题。
The text was updated successfully, but these errors were encountered: