hyperopt-sklearn | Hyper-parameter optimization for sklearn | Machine Learning library
kandi X-RAY | hyperopt-sklearn Summary
kandi X-RAY | hyperopt-sklearn Summary
hyperopt-sklearn is a Python library typically used in Artificial Intelligence, Machine Learning applications. hyperopt-sklearn has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However hyperopt-sklearn has a Non-SPDX License. You can download it from GitHub.
Hyperopt-sklearn is Hyperopt-based model selection among machine learning algorithms in scikit-learn. See how to use hyperopt-sklearn through examples or older notebooks. More examples can be found in the Example Usage section of the SciPy paper. Komer B., Bergstra J., and Eliasmith C. "Hyperopt-Sklearn: automatic hyperparameter configuration for Scikit-learn" Proc. SciPy 2014.
Hyperopt-sklearn is Hyperopt-based model selection among machine learning algorithms in scikit-learn. See how to use hyperopt-sklearn through examples or older notebooks. More examples can be found in the Example Usage section of the SciPy paper. Komer B., Bergstra J., and Eliasmith C. "Hyperopt-Sklearn: automatic hyperparameter configuration for Scikit-learn" Proc. SciPy 2014.
Support
Quality
Security
License
Reuse
Support
hyperopt-sklearn has a medium active ecosystem.
It has 1431 star(s) with 258 fork(s). There are 57 watchers for this library.
It had no major release in the last 6 months.
There are 72 open issues and 58 have been closed. On average issues are closed in 101 days. There are 7 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of hyperopt-sklearn is 0.0.3
Quality
hyperopt-sklearn has 0 bugs and 0 code smells.
Security
hyperopt-sklearn has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
hyperopt-sklearn code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
hyperopt-sklearn has a Non-SPDX License.
Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.
Reuse
hyperopt-sklearn releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
hyperopt-sklearn saves you 1263 person hours of effort in developing the same functionality from scratch.
It has 6449 lines of code, 629 functions and 152 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed hyperopt-sklearn and discovered the below as its top functions. This is intended to give you an instant insight into hyperopt-sklearn implemented functionality, and help decide if they suit your requirements.
- Calculate cost function
- Perform training until convergence
- Determine if we should stop early
- Check if convergence is met
- Return a list of all classifiers
- Construct a bagger classifier
- Random seed state
- Create a DecisionTree classifier
- Return a list of all regressors
- Check if lightgbm is installed
- Check if xgboost is installed
- Create a new bagging regressor
- List all preprocessors
- Wrapper for sklearn_maxAbsScaler
- Create a new binarizer
- Create an output classifier
- Return a random classifier
- Return a list of forest classifiers
- Select a sparse preprocessing
- Choose a sparse regressor
- Select preprocessing
- Return a list of a forest regressor
- Return a possibly - dense classifier
- Fit the model
- Return a random regression
- Generate text preprocessing
Get all kandi verified functions for this library.
hyperopt-sklearn Key Features
No Key Features are available at this moment for hyperopt-sklearn.
hyperopt-sklearn Examples and Code Snippets
No Code Snippets are available at this moment for hyperopt-sklearn.
Community Discussions
Trending Discussions on hyperopt-sklearn
QUESTION
How to install HyperOpt-Sklearn library in Google Collab?
Asked 2020-Oct-19 at 17:48
Every time I try to install HyperOpt-Sklearn library in Google Collab, I get the following error:
...ANSWER
Answered 2020-Oct-19 at 17:48Although not mentioned in their documentation, turns out the package is available at PyPi and it can be installed simply by pip; the following is run in a Google Colab notebook:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install hyperopt-sklearn
Installation from the GitHub repository is supported using pip:.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
Find more information at:
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
