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Uploading an XGBoost Model Artifact

Note

For more information on uploading a model artifact to Fiddler, see Uploading a Model Artifact

Suppose you would like to upload a model artifact for a XGBoost model.

Following is an example of what the package.py script may look like.

import pickle
from pathlib import Path
import pandas as pd
import xgboost as xgb

PACKAGE_PATH = Path(__file__).parent

OUTPUT_COLUMN = ['probability_over_50k']

class MyModel:

    def __init__(self):

        # Load the model
        with open(PACKAGE_PATH / 'model.pkl', 'rb') as pkl_file:
            self.model = pickle.load(pkl_file)

    def transform_input(self, input_df):

        # Convert DataFrame to XGBoost DMatrix
        transformed_input = xgb.DMatrix(input_df)

    def predict(self, input_df):

        # Apply data transformation
        transformed_input = self.transform_input(input_df)

        # Store predictions in a DataFrame
        return pd.DataFrame(self.model.predict(transformed_input), columns=OUTPUT_COLUMN)

def get_model():
    return MyModel()
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