Normalize¶
fast step math
Normalizes a numerical column by subtracting the mean and dividing by its standard deviation.
The resulting column's values will have a mean of 0.0 and a standard deviation of 1.0.
Both types of scaling can be toggled separately via the with_mean
and with_std
parameters.
Usage¶
The following are the step's expected inputs and outputs and their specific types.
normalize(input: number, {"param": value}) -> (output: number)
where the object {"param": value}
is optional in most cases and if present may contain any of the parameters described in the
corresponding section below.
Example¶
To normalize using both mean and standard deviation:
normalize(ds.input) -> (ds.normalized)
More examples
Using a custom configuration to only subtract the mean:
normalize(ds.input, {
"with_mean": true,
"with_std": false,
}) -> (ds.normalized)
Inputs¶
input: column:number
A numeric column to normalize.
Outputs¶
output: column:number
A numeric column containing the normalized value.
Parameters¶
with_mean: boolean = True
Whether to subtract the mean.
with_std: boolean = True
Whether to divide by the standard deviation.