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Databricks Exam Databricks Machine Learning Associate Topic 1 Question 34 Discussion

Actual exam question for Databricks's Databricks Machine Learning Associate exam
Question #: 34
Topic #: 1
[All Databricks Machine Learning Associate Questions]

A data scientist wants to efficiently tune the hyperparameters of a scikit-learn model. They elect to use the Hyperopt library's fmin operation to facilitate this process. Unfortunately, the final model is not very accurate. The data scientist suspects that there is an issue with the objective_function being passed as an argument to fmin.

They use the following code block to create the objective_function:

Which of the following changes does the data scientist need to make to their objective_function in order to produce a more accurate model?

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Suggested Answer: D

When using the Hyperopt library with fmin, the goal is to find the minimum of the objective function. Since you are using cross_val_score to calculate the R2 score which is a measure of the proportion of the variance for a dependent variable that's explained by an independent variable(s) in a regression model, higher values are better. However, fmin seeks to minimize the objective function, so to align with fmin's goal, you should return the negative of the R2 score (-r2). This way, by minimizing the negative R2, fmin is effectively maximizing the R2 score, which can lead to a more accurate model.

Reference

Hyperopt Documentation: http://hyperopt.github.io/hyperopt/

Scikit-Learn documentation on model evaluation: https://scikit-learn.org/stable/modules/model_evaluation.html


by Marshall at Aug 12, 2025, 09:01 AM

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Celia
2 days ago
I'm not entirely sure, but I think removing the mean operation around cross_val_score might be necessary. It could be skewing the results somehow.
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Larue
8 days ago
I remember we discussed the importance of validation sets in tuning hyperparameters. Adding a test set validation process could really help improve accuracy.
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Abraham
13 days ago
Hmm, this is an interesting challenge. I think the key might be to replace the r2 return value with -r2. That could help the optimization process find a more accurate model. I'll give that a try and see how it goes.
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Pearly
18 days ago
I'm a bit confused by this one. There are a few different options, and I'm not sure which one is the right approach. I'll need to carefully read through the question and the code to try to figure out the best solution.
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Yuette
23 days ago
Alright, this is a good one. I think the issue might be with the mean operation wrapping the cross_val_score. I'll need to explore that a bit more to see if that's the root of the problem.
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Kiley
28 days ago
Okay, let's see here. The key seems to be identifying what's wrong with the objective function that's being passed to fmin. I'll need to consider the different options and think through the implications of each.
upvoted 0 times
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Inocencia
1 month ago
Hmm, this looks like a tricky one. I'll need to carefully review the code and think through the potential issues with the objective function.
upvoted 0 times
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