Write Readable Tests for Your Machine Learning Models with Behave

Use natural language to test the behavior of your ML models

Motivation

Imagine you create an ML model to predict customer sentiment based on reviews. Upon deploying it, you realize that the model incorrectly labels certain positive reviews as negative when they’re rephrased using negative words.

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This is just one example of how an extremely accurate ML model can fail without proper testing. Thus, testing your model for accuracy and reliability is crucial before deployment.

But how do you test your ML model? One straightforward approach is to use unit-test:

from textblob import TextBlob


def test_sentiment_the_same_after_paraphrasing():
    sent = "The hotel room was great! It was spacious, clean and had a nice view of the city."
    sent_paraphrased = "The hotel room wasn't bad. It wasn't cramped, dirty, and had a decent view of the city."
    
    sentiment_original = TextBlob(sent).sentiment.polarity…