scikit-mice
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MICE Imputation implementation using scikit learn.
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Scikit-mice
Scikit-mice runs the MICE imputation algorithm. Based on the following paper.
Documentation:
The MiceImputer class is similar to the sklearn Imputer class.
MiceImputer has the same instantiation parameters as Imputer.
The MiceImputer.transform() function takes in three arguments.
| Param | Type | Description |
|---|---|---|
X |
matrix |
Numpy matrix or python matrix of data. |
model_class |
class |
Scikit-learn model class. |
iterations |
int |
Int for numbe of interations to run. |
What is returned by MiceImputer is a tuple of imputed values as well as a matrix of model performance for each iteration and column.
(imputed_x, model_specs_matrix)
Example:
from sklearn.linear_model import LinearRegression
import skmice
imputer = MiceImputer()
X = [[1, 2], [np.nan, 3], [7, 6]]
X, specs = imputer.transform(X, LinearRegression, 10)
print specs
What is returned is a MICE imputed matrix running 10 iterations using a simple LinearRegression.
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