LogitScaler

Compatibility: numerical data

The LogitScaler performs a statistical transformation on numerical data. It computes the Logit function to convert the scale and shape of the data. You can optionally choose the min and max values of the Logit function, effectively enforcing the min/max boundaries on your data.

from rdt.transformers.numerical import LogitScaler

transformer = LogitScaler(min_value=0, max_value=100)

Parameters

missing_value_replacement: Add this argument to replace missing values during the transform phase

(default) 'mean'	Replace all missing values with the average value.
'random'	Replace missing values with a random value. The value is chosen uniformly at random from the min/max range.
'mode'	Replace all missing values with the most frequently occurring value
<number>	Replace all missing values with the specified number (0, -1, 0.5, etc.)
None	Do not replace missing values. The transformed data will continue to have missing values.

missing_value_generation: Add this argument to determine how to recreate missing values during the reverse transform phase

(default) 'random'	Randomly assign missing values in roughly the same proportion as the original data.
'from_column'	Create a new column to store whether the value should be missing. Use it to recreate missing values. Note: Adding extra columns uses more memory and increases the RDT processing time.
None	Do not recreate missing values.

min_value: The min value for the Logit function. The Logit function of anything ≤ this value is undefined.

(default) 0	The min value of the function is 0.
<float>	A floating point value that acts as as the min value of the Logit function.

max_value: The max value for the Logit function. The Logit function of anything ≥ this value is undefined.

(default) 1	The max value of the function is 0.
<float>	A floating point value that acts as as the max value of the Logit function.

learn_rounding_scheme: Add this argument to allow the transformer to learn about rounded values in your dataset.

(default) False	Do not learn or enforce any rounding scheme. When reverse transforming the data, there may be many decimal places present.
True	Learn the rounding rules from the input data. When reverse transforming the data, round the number of digits to match the original.

FAQ

How do I enforce min/max values with this transformer?

This transformer enforces strict minimum and maximum boundaries on your data using the min_value and max_value parameters.

If you'd like the minimum or maximum value to be allowed, we suggest setting the boundary to something slightly outside the range that you need.

from rdt.transformers.numerical import LogitScaler
transformer = LogitScaler(
    min_value=0.0 - 1e-10, # allow a value of exactly 0 
    max_value=10.0 + 1e-10 # allow a value of exactly 10
)

If you'd like to enforce singular boundary (min or max) instead, please use the LogScaler.