numpy-ml collects machine learning algorithms in NumPy, presented as an intentionally readable Python package.
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24 alternativeshyperopt
hyperopt-sklearn uses hyperparameter optimization to select machine learning algorithms for scikit-learn.
About hyperopt
hyperopt-sklearn is a Python repository on GitHub that uses hyperparameter optimization to select machine learning algorithms in scikit-learn. According to its README, adding the hyperparameter search to a standard scikit-learn workflow requires only a one-line change, using a HyperoptEstimator wrapper around a classifier.
Each component comes with a default search space, which users can change or hold constant by passing keyword arguments. The README includes examples using the Iris dataset and a handwritten digits dataset, and the package can be installed with pip, including from a specific tag, branch, or commit.
Key features
- Model selection among scikit-learn algorithms using hyperparameter optimization
- HyperoptEstimator wrapper that adds the search to a scikit-learn classifier
- Default search space for each component
- Keyword arguments to change or fix individual parameter search spaces
- Search across any_classifier and any_preprocessing options
- Configurable number of evaluations and per-trial timeout
Best for: Python developers who already use scikit-learn and want automated hyperparameter search for model selection.
Good for
- Adding the hyperparameter search to a standard scikit-learn workflow is described as a one-line change.
- Each component includes a default search space that users can modify.
hyperopt at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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hyperopt FAQ
How do I add hyperparameter search to an existing scikit-learn workflow?
According to the README, it is a one-line change from the standard pipeline: wrap the classifier in a HyperoptEstimator, such as HyperoptEstimator(classifier=svc("mySVC")).
Can a parameter be held fixed during the search?
Yes. Passing a value as a keyword argument holds that parameter constant, and the README gives an example where the penalty parameter is fixed while other parameters are searched.
How can a specific version be installed?
The README states that pip can install from the GitHub repository at a specific tag, branch, or commit, using a pip install git+ command with the version reference appended.
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