Databricks Machine Learning Professional exam dumps

Databricks Machine Learning Professional practice question 261 of 280

Databricks Certified Machine Learning Professional. Professional level, Databricks. Free question with the correct answer and a full explanation.

Databricks Machine Learning Professional Question 261

Single answer

You are working on a machine learning project aimed at predicting customer churn for a subscription-based service. You have categorical data on customer demographics, such as 'Subscription Type' (Basic, Premium, Enterprise) and 'Churn' (Yes, No). Which scenario would be most appropriate for using a chi-square test?

  1. A

    To determine if the 'Subscription Type' is independent of 'Churn'.

  2. B

    To evaluate the correlation between 'Churn' and the customer's monthly expenditure.

  3. C

    To assess whether 'Subscription Type' affects the model's accuracy after training.

  4. D

    To test if the distribution of 'Subscription Type' matches the expected distribution in a new dataset.

Show answer and explanation

Correct answer: A

Explanation

The chi-square test is a statistical method used to determine if there is a significant association between two categorical variables. In this scenario, 'Subscription Type' and 'Churn' are both categorical, making the chi-square test appropriate for assessing whether they are independent of each other. This insight can inform feature selection or preprocessing steps in the machine learning pipeline.

  • A. Correct.

    Correct: A chi-square test is used to evaluate the independence between two categorical variables, such as 'Subscription Type' and 'Churn'.

  • B. Incorrect.

    Incorrect: Correlation is typically measured for continuous variables, and the chi-square test is not suitable for this purpose.

  • C. Incorrect.

    Incorrect: Assessing model accuracy is not related to the chi-square test, as it does not involve testing relationships between categorical features.

  • D. Incorrect.

    Incorrect: Testing if a distribution matches an expected distribution would involve a goodness-of-fit test, not a test of independence.

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