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Last active January 28, 2020 14:20
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# Define the Pipeline
Step1: get the oultet binary columns
Step2: pre processing
Step3: Train a Random Forest Model
model_pipeline = Pipeline(steps=[('get_outlet_binary_columns', OutletTypeEncoder()),
('random_forest', RandomForestRegressor(max_depth=10,random_state=2))
# fit the pipeline with the training data,train_y)
# predict target values on the training data
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