Answer-first summary for fast verification
Answer: SparkTrials
The **SparkTrials** class in Hyperopt is designed for parallelizing hyperparameter searches across a Spark cluster, making it the optimal choice for concurrent optimization. Other options like `fmin`, `Search Space`, `hp.quniform`, and `Trials` are part of Hyperopt but do not specifically facilitate parallel optimization. - **Option A (fmin)**: Incorrect. `fmin` is used for minimizing an objective function, not for parallel optimization. - **Option B (Search Space)**: Incorrect. Defines the hyperparameter space but does not handle parallel optimization. - **Option C (hp.quniform)**: Incorrect. Specifies a quantized uniform distribution for hyperparameters but does not enable parallel processing. - **Option E (Trials)**: Incorrect. Stores optimization results but does not perform parallel optimization.
Author: LeetQuiz Editorial Team
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A data scientist aims to fine-tune the hyperparameters of a scikit-learn model efficiently and concurrently using the Hyperopt library. Which Hyperopt tool enables parallel hyperparameter optimization?
A
fmin
B
Search Space
C
hp.quniform
D
SparkTrials
E
Trials
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