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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 |
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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 |
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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 |
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ValueError: If output_min, output_max have the wrong order.
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