andre/100-Days-Of-ML-Code
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new version of scikit-learn api

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Yong Mao
2020-02-18 09:44:49 +08:00
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parent a293223107
commit 71e0465c9b
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Code/Day 1_Data_Preprocessing.py
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@ -15,6 +15,9 @@ print("Y")
print(Y) print(Y)
#Step 3: Handling the missing data #Step 3: Handling the missing data
# If you use the newest version of sklearn, use the lines of code commented out
# from sklearn.impute import SimpleImputer
# imputer = SimpleImputer(missing_values="NaN", strategy="mean")
from sklearn.preprocessing import Imputer from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values = "NaN", strategy = "mean", axis = 0) imputer = Imputer(missing_values = "NaN", strategy = "mean", axis = 0)
imputer = imputer.fit(X[ : , 1:3]) imputer = imputer.fit(X[ : , 1:3])