tf.contrib.linear_optimizer.SparseFeatureColumn

Represents a sparse feature column.

Contains three tensors representing a sparse feature column, they are example indices (int64), feature indices (int64), and feature values (float). Feature weights are optional, and are treated as 1.0f if missing.

For example, consider a batch of 4 examples, which contains the following features in a particular SparseFeatureColumn:

  • Example 0: feature 5, value 1
  • Example 1: feature 6, value 1 and feature 10, value 0.5
  • Example 2: no features
  • Example 3: two copies of feature 2, value 1

This SparseFeatureColumn will be represented as follows:

<0, 5,  1>
<1, 6,  1>
<1, 10, 0.5>
<3, 2,  1>
<3, 2,  1>

For a batch of 2 examples below:

  • Example 0: feature 5
  • Example 1: feature 6

is represented by SparseFeatureColumn as:

<0, 5,  1>
<1, 6,  1>

Args
example_indices A 1-D int64 tensor of shape [N]. Also, accepts python lists, or numpy arrays.
feature_indices A 1-D int64 tensor of shape [N]. Also, accepts python lists, or numpy arrays.
feature_values An optional 1-D tensor float tensor of shape [N]. Also, accepts python lists, or numpy arrays.
Attributes
example_indices The example indices represented as a dense tensor.
feature_indices The feature indices represented as a dense tensor.
feature_values The feature values represented as a dense tensor.

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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/linear_optimizer/SparseFeatureColumn