machine-learning - tensorflow 估计器 : training with weighted examples

Question

我正在使用 Tensorflow Estimator 训练模型，但我的数据不平衡。我想通过对每个训练示例进行加权来纠正这个问题。

在原始 Tensorflow 中，人们可能会做到 like this 。在 Estimator 中是否有一种简单的方法可以做到这一点？也许构建一个自定义的input_fn？

Answer 1

我假设你正在做分类。如果是这样，请使用 tf.estimator.DNNClassifier :

weight_column: A string or a _NumericColumn created by tf.feature_column.numeric_column defining feature column representing weights. It is used to down weight or boost examples during training. It will be multiplied by the loss of the example. If it is a string, it is used as a key to fetch weight tensor from the features. If it is a _NumericColumn, raw tensor is fetched by key weight_column.key, then weight_column.normalizer_fn is applied on it to get weight tensor.