tf.compat.v1.estimator.DNNRegressor

A regressor for TensorFlow DNN models.

Inherits From: Estimator

Example:

categorical_feature_a = categorical_column_with_hash_bucket(...)
categorical_feature_b = categorical_column_with_hash_bucket(...)

categorical_feature_a_emb = embedding_column(
    categorical_column=categorical_feature_a, ...)
categorical_feature_b_emb = embedding_column(
    categorical_column=categorical_feature_b, ...)

estimator = tf.estimator.DNNRegressor(
    feature_columns=[categorical_feature_a_emb, categorical_feature_b_emb],
    hidden_units=[1024, 512, 256])

# Or estimator using the ProximalAdagradOptimizer optimizer with
# regularization.
estimator = tf.estimator.DNNRegressor(
    feature_columns=[categorical_feature_a_emb, categorical_feature_b_emb],
    hidden_units=[1024, 512, 256],
    optimizer=tf.compat.v1.train.ProximalAdagradOptimizer(
      learning_rate=0.1,
      l1_regularization_strength=0.001
    ))

# Or estimator using