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# importing required libraries | |
import pandas as pd | |
from sklearn.compose import ColumnTransformer | |
from sklearn.impute import SimpleImputer | |
import category_encoders as ce | |
from sklearn.preprocessing import StandardScaler | |
from sklearn.ensemble import RandomForestRegressor | |
from sklearn.pipeline import Pipeline | |
# read the training data set | |
data = pd.read_csv('dataset/train_kOBLwZA.csv') | |
# top rows of the data | |
data.head() | |
# seperate the independent and target variables | |
train_x = data.drop(columns=['Item_Outlet_Sales']) | |
train_y = data['Item_Outlet_Sales'] |
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