Exam Certified Machine Learning Associate topic 1 question 23 discussion

Actual exam question from Databricks's Certified Machine Learning Associate

Question #: 23
Topic #: 1

[All Certified Machine Learning Associate Questions]

A data scientist wants to tune a set of hyperparameters for a machine learning model. They have wrapped a Spark ML model in the objective function objective_function and they have defined the search space search_space.
As a result, they have the following code block:

Which of the following changes do they need to make to the above code block in order to accomplish the task?

A. Change SparkTrials() to Trials()
B. Reduce num_evals to be less than 10
C. Change fmin() to fmax()
D. Remove the trials=trials argument
E. Remove the algo=tpe.suggest argument

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Suggested Answer: A 🗳️

by [deleted] at May 31, 2024, 9:36 p.m.

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5 months, 4 weeks ago

Selected Answer: A

Option A is correct. Trying to use SparkTrials when the objective function itself uses Spark ML would give errors. From Hyperopt documentation "Since SparkTrials fits and evaluates each model on one Spark worker, it is limited to tuning single-machine ML models and workflows, such as scikit-learn or single-machine TensorFlow. For distributed ML algorithms such as Apache Spark MLlib or Horovod, you can use Hyperopt’s default Trials class." https://hyperopt.github.io/hyperopt/scaleout/spark/

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Exam Certified Machine Learning Associate topic 1 question 23 discussion

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