A Flask API for serving scikit-learn models
Amir Ziai

Hi Amir,

I’m attempting to wrap my binary classifier in an API using the steps shown here.

My input to the API is a single string, and the output should be 0 or 1.

When I attempt to run this code:

query_df = pd.DataFrame(np.array([‘my string’]))

query = pd.get_dummies(query_df)
result = loaded_model.predict(query)

I get the error:

ValueError: Number of features of the model must match the input. Model n_features is 16413 and input n_features is 1

Are there additional steps I must take in shaping the input data into loaded_model.predict()?

My classifier is trained on single string features and binary labels (0 or 1).

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