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Uploading a Binary Classification 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 binary classification model.

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

import pickle
from pathlib import Path
import pandas as pd
from sklearn.linear_model import LogisticRegression

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 predict(self, input_df):

        # Store predictions in a DataFrame
        return pd.DataFrame(self.model.predict_proba(input_df)[:, 1], columns=OUTPUT_COLUMN)

def get_model():
    return MyModel()

Here, we are assuming that the model prediction column that has been specified in the fdl.ModelInfo object is called probability_over_50k.

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