explainy | Python library for generating machine learning model
kandi X-RAY | explainy Summary
kandi X-RAY | explainy Summary
explainy is a Python library. explainy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install explainy' or download it from GitHub, PyPI.
explainy is a library for generating machine learning models explanations in Python. It uses methods from Machine Learning Explainability and provides a standardized API to create feature importance explanations for samples. The API is inspired by scikit-learn and has three core methods explain(), plot() and, importance(). The explanations are generated in the form of texts and plots. explainy comes with four different algorithms to create either global or local and contrastive or non-contrastive model explanations. | Method |Type | Explanations | Classification | Regression | | --- | --- | :---: | :---: | :---: | |Permutation Feature Importance | non-contrastive | global | :star: | :star:| |Shap Values | non-contrastive | local | :star: | :star:| |Surrogate Model|contrastive | global | :star: | :star: | |Counterfactual Example| contrastive | local |:star:| :star:|.
explainy is a library for generating machine learning models explanations in Python. It uses methods from Machine Learning Explainability and provides a standardized API to create feature importance explanations for samples. The API is inspired by scikit-learn and has three core methods explain(), plot() and, importance(). The explanations are generated in the form of texts and plots. explainy comes with four different algorithms to create either global or local and contrastive or non-contrastive model explanations. | Method |Type | Explanations | Classification | Regression | | --- | --- | :---: | :---: | :---: | |Permutation Feature Importance | non-contrastive | global | :star: | :star:| |Shap Values | non-contrastive | local | :star: | :star:| |Surrogate Model|contrastive | global | :star: | :star: | |Counterfactual Example| contrastive | local |:star:| :star:|.
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Support
explainy has a low active ecosystem.
It has 16 star(s) with 0 fork(s). There are 3 watchers for this library.
There were 1 major release(s) in the last 6 months.
There are 0 open issues and 1 have been closed. On average issues are closed in 48 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of explainy is 0.2.9
Quality
explainy has no bugs reported.
Security
explainy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
explainy is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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explainy releases are not available. You will need to build from source code and install.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
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explainy Key Features
No Key Features are available at this moment for explainy.
explainy Examples and Code Snippets
No Code Snippets are available at this moment for explainy.
Community Discussions
No Community Discussions are available at this moment for explainy.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install explainy
You can install using 'pip install explainy' or download it from GitHub, PyPI.
You can use explainy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use explainy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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 .
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