MeanStdevScaler

class mastml.legos.feature_normalizers.MeanStdevScaler(features=None, mean=0, stdev=1)

Bases: sklearn.base.BaseEstimator, sklearn.base.TransformerMixin

Class designed to normalize input data to a specified mean and standard deviation

Args:

mean: (int/float), specified normalized mean of the data

stdev: (int/float), specified normalized standard deviation of the data

Methods:

fit: Obtains initial mean and stdev of data

Args:

df: (dataframe), dataframe of values to be normalized

Returns:

(self, the object instance)

transform: Normalizes the data to new mean and stdev values

Args:

df: (dataframe), dataframe of values to be normalized

Returns:

(dataframe), dataframe containing re-normalized data and any data that wasn’t normalized

inverse_transform: Un-normalizes the data to the old mean and stdev values

Args:

df: (dataframe), dataframe of values to be un-normalized

Returns:

(dataframe), dataframe containing un-normalized data and any data that wasn’t normalized

Methods Summary

fit(df[, y])
inverse_transform(df)
transform(df)

Methods Documentation

fit(df, y=None)

inverse_transform(df)

transform(df)