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Tejas-Deo/etr_itr_imputer.py

Created December 3, 2020 09:34
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To use Iterative Imputer with ExtratReesRegressor as the estimator to impute the missing value (missing percentage between 5 to 30%)
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etr_itr_imputer.py
from sklearn.experimental import enable_iterative_imputer
from sklearn.impute import IterativeImputer
from sklearn.ensemble import ExtraTreesRegressor
etr = ExtraTreesRegressor(n_estimators = 50, n_jobs = -1)
etr_itr_imputer = IterativeImputer(estimator = etr, max_iter = 4, random_state = 0, tol = 1e-5, verbose = 2)
trained_etr_itr_imputer = etr_itr_imputer.fit(measures_df_less_than_30_percent_train)
X_train_7_imputed = trained_etr_itr_imputer.transform(measures_df_less_than_30_percent_train)
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