logistic_regressor_test.py 文件源码

def _logistic_regression_model_fn(features, labels):
  logits = tf.contrib.layers.linear(
      features,
      1,
      weights_initializer=tf.zeros_initializer,
      # Intentionally uses really awful initial values so that
      # AUC/precision/recall/etc will change meaningfully even on a toy dataset.
      biases_initializer=tf.constant_initializer(-10.0))
  predictions = tf.sigmoid(logits)
  loss = tf.contrib.losses.sigmoid_cross_entropy(logits, labels)
  train_op = tf.contrib.layers.optimize_loss(
      loss,
      tf.contrib.framework.get_global_step(),
      optimizer='Adagrad',
      learning_rate=0.1)
  return predictions, loss, train_op