Class SparseFeatureColumn
Defined in tensorflow/contrib/linear_optimizer/python/ops/sparse_feature_column.py
.
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>
__init__
__init__(
example_indices,
feature_indices,
feature_values
)
Creates a SparseFeatureColumn
representation. (deprecated)
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.
Returns:
A SparseFeatureColumn
Properties
example_indices
The example indices represented as a dense tensor.
Returns:
A 1-D Tensor of int64 with shape [N]
.
feature_indices
The feature indices represented as a dense tensor.
Returns:
A 1-D Tensor of int64 with shape [N]
.
feature_values
The feature values represented as a dense tensor.
Returns:
May return None, or a 1-D Tensor of float32 with shape [N]
.