Imputer¶
Some of the docstrings for this module have been automatically extracted from the scikit-learn library and are covered by their respective licenses.
-
class
node_preprocessing.
Imputer
[source]¶ Replaces missing values in a dataset with a computed value infered from the remained of the dataset.
Configuration: missing_values
The placeholder for the missing values. All occurrences of missing_values will be imputed. For missing values encoded as np.nan, use the string value “NaN”.
strategy
The imputation strategy.
- If “mean”, then replace missing values using the mean along the axis.
- If “median”, then replace missing values using the median along the axis.
- If “most_frequent”, then replace missing using the most frequent value along the axis.
axis
The axis along which to impute.
- If axis=0, then impute along columns.
- If axis=1, then impute along rows.
Attributes: statistics_
The imputation fill value for each feature if axis == 0.
Inputs: Outputs: - model : model
Model