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Update Day 1_Data_Preprocessing.py

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yx-xyc
2021-01-14 10:59:16 +08:00
parent 524c84e8a9
commit 13020158fe
1 changed files with 2 additions and 2 deletions
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Code/Day 1_Data_Preprocessing.py
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@ -19,7 +19,7 @@ print(Y)
# from sklearn.impute import SimpleImputer # from sklearn.impute import SimpleImputer
# imputer = SimpleImputer(missing_values="NaN", strategy="mean") # 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 = np.nan, strategy = "mean", axis = 0)
imputer = imputer.fit(X[ : , 1:3]) imputer = imputer.fit(X[ : , 1:3])
X[ : , 1:3] = imputer.transform(X[ : , 1:3]) X[ : , 1:3] = imputer.transform(X[ : , 1:3])
print("---------------------") print("---------------------")
@ -33,7 +33,7 @@ from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_X = LabelEncoder() labelencoder_X = LabelEncoder()
X[ : , 0] = labelencoder_X.fit_transform(X[ : , 0]) X[ : , 0] = labelencoder_X.fit_transform(X[ : , 0])
#Creating a dummy variable #Creating a dummy variable
onehotencoder = OneHotEncoder(categorical_features = [0]) onehotencoder = OneHotEncoder('auto')
X = onehotencoder.fit_transform(X).toarray() X = onehotencoder.fit_transform(X).toarray()
labelencoder_Y = LabelEncoder() labelencoder_Y = LabelEncoder()
Y = labelencoder_Y.fit_transform(Y) Y = labelencoder_Y.fit_transform(Y)