Scale a numerical column into the range [output_min, output_max].
tft.scale_by_min_max(
x: common_types.ConsistentTensorType,
output_min: float = 0.0,
output_max: float = 1.0,
elementwise: bool = False,
name: Optional[str] = None
) -> common_types.ConsistentTensorType
Args |
x
|
A numeric Tensor , SparseTensor , or RaggedTensor .
|
output_min
|
The minimum of the range of output values.
|
output_max
|
The maximum of the range of output values.
|
elementwise
|
If true, scale each element of the tensor independently.
|
name
|
(Optional) A name for this operation.
|
Returns |
A Tensor containing the input column scaled to [output_min, output_max].
If the analysis dataset is empty or contains a singe distinct value, then
x is scaled using a sigmoid function.
|
Raises |
ValueError
|
If output_min, output_max have the wrong order.
|