MeanStdevScaler¶
- class mastml.preprocessing.MeanStdevScaler(mean=0, stdev=1, as_frame=False)[source]¶
Bases:
BasePreprocessor
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_transform
(X[, y])Fit to data, then transform it.
Methods Documentation
- fit_transform(X, y=None, **fit_params)[source]¶
Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.
Parameters¶
- Xarray-like of shape (n_samples, n_features)
Input samples.
- yarray-like of shape (n_samples,) or (n_samples, n_outputs), default=None
Target values (None for unsupervised transformations).
- **fit_paramsdict
Additional fit parameters.
Returns¶
- X_newndarray array of shape (n_samples, n_features_new)
Transformed array.