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Returns a standardized column with mean 0 and variance 1.
tft.scale_to_z_score( x: common_types.ConsistentTensorType, elementwise: bool = False, name: Optional[str] = None, output_dtype: Optional[tf.DType] = None ) -> common_types.ConsistentTensorType
Scaling to z-score subtracts out the mean and divides by standard deviation. Note that the standard deviation computed here is based on the biased variance (0 delta degrees of freedom), as computed by analyzers.var.
||If true, scales each element of the tensor independently; otherwise uses the mean and variance of the whole tensor.|
||(Optional) A name for this operation.|
||(Optional) If not None, casts the output tensor to this type.|
Note that TFLearn generally permits only tf.int64 and tf.float32, so casting this scaler's output may be necessary.