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argueview-0.2.1
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مشاهده بیشترتوضیحات
ArgueView is a tool for generating text-based presentations for machine-learning predictions and feature-importance based explanation tools. The tool makes use of Toulmin's model of argumentation for structuring the text-based explanations.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | argueview-0.2.1 |
| نام | argueview |
| نسخه کتابخانه | 0.2.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Sophia Hadash |
| ایمیل نویسنده | s.hadash@tue.nl |
| آدرس صفحه اصلی | https://github.com/SophiaHadash/ArgueView |
| آدرس اینترنتی | https://pypi.org/project/argueview/ |
| مجوز | - |
<p align="center">
<img href="https://github.com/SophiaHadash/ArgueView" alt="ArgueView" src="https://raw.githubusercontent.com/SophiaHadash/ArgueView/master/screenshots/logo.svg" width="50%" />
<p>
---
[](https://jenkins.tuneblendr.com/blue/organizations/jenkins/ArgueView/activity)
ArgueView is a tool for generating text-based presentations for machine-learning predictions and feature-importance based explanation tools. The tool makes use of Toulmin's model of argumentation for structuring the text-based explanations.
Example output using the visualizer:
The procedure for creating ArgueView explanations is as follows:
1. A traditional machine-learning context is created (i.e. data, model)
2. An explainer is employed to produce *feature importance*. This can be a white-box or black-box explainer. An example of a black-box explainer is [LIME](https://github.com/marcotcr/lime).
3. The machine-learning context and the *feature importance* are given to ArgueView such that it can produce a textual explanation.
## Installation
ArgueView is available as a python package on [PyPi](https://pypi.org/project/argueview/). You can install it using `pip`:
```
pip install argueview
```
Or, using `pipenv`:
```
pipenv install argueview
```
## Usage
Usage is documented in our examples. Examples are available in python and jupyter notebooks. The following examples are available:
- minimal, hypothetical data and explainer: [python](https://github.com/SophiaHadash/ArgueView/blob/master/examples/fruit_plain/example.py)
- creditg data with [LIME](https://github.com/marcotcr/lime) explainer: [python](https://github.com/SophiaHadash/ArgueView/blob/master/examples/creditg_lime/example.py), [notebook](https://github.com/SophiaHadash/ArgueView/blob/master/examples/creditg_lime/example.ipynb)
- creditg data with [shap](https://github.com/slundberg/shap) explainer: [python](https://github.com/SophiaHadash/ArgueView/blob/master/examples/creditg_shap/example.py), [notebook](https://github.com/SophiaHadash/ArgueView/blob/master/examples/creditg_shap/example.ipynb)
## Running the examples
There are two examples available to help you learn how to use ArgueView. The 'plain' examples uses hypothetical data to show a minimalistic use-case. The CreditG example uses real data and a real ML model to illustrate a real-world use case.
If you would like to run the CreditG example the script needs to obtain the data. For this we use [OpenML](https://www.openml.org/). However, usage requires a valid API key and you will need to obtain one to run the example.
After you have obtained your key, create a `.env` file with your [OpenML](https://www.openml.org/) API key.
```
echo "OML_APIKEY={my-key}" > .env
```
*Note: You can skip this step if you want to run the hypothetical example.*
Install all dependencies:
```
pipenv install --dev
```
Run an example:
```
/path/to/python3 ./examples/{example}/example.py
```
Additionally, there is are Jupyther Notebooks available to directly see how ArgueView works.
## Building
Follow these steps to build ArgueView from source.
- make sure you install the dependencies. ArgueView requires the following dependencies: `python>=3.5`, `pip3`, `pipenv`, `git`.
- build using make
```
make
```
### Using Docker
Alternatively you can build ArgueView using docker.
- build context dockerfile
```
docker build -t argueview/context:local .
```
- run `build.sh` in a container
```
CID=$(docker run
-v /var/run/docker.sock:/var/run/docker.sock
argueview/context
build.sh)
```
- copy results from the container
```
docker cp ${CID}:/argueview/argueview.egg-info ./argueview.egg-info
docker cp ${CID}:/argueview/build ./build
docker cp ${CID}:/argueview/dist ./dist
```
نیازمندی
| مقدار | نام |
|---|---|
| ==0.0.2.0 | anchor-exp |
| ==0.2.0 | backcall |
| ==2020.12.5 | certifi |
| ==3.0.4 | chardet |
| ==0.10.0 | cycler |
| ==2.0.5 | cymem |
| ==4.4.2 | decorator |
| ==2.9.0 | imageio |
| ==0.2.0 | ipython-genutils |
| ==7.19.0 | ipython |
| ==1.4.1 | jsonpickle |
| ==1.0.5 | murmurhash |
| ==1.19.4 | numpy |
| ==0.7.5 | pickleshare |
| ==1.1.3 | plac |
| ==3.0.5 | preshed |
| ==0.6.0 | ptyprocess |
| ==1.5.4 | scipy |
| ==1.0.5 | srsly |
| ==7.4.3 | thinc |
| ==0.8.0 | wasabi |
| ==0.2.5 | wcwidth |
| ==3.0.8 | prompt-toolkit |
| ==2.4.7 | pyparsing |
| ==1.0.0 | catalogue |
| ==2.10 | idna |
| ==0.7.1 | parso |
| ==2.8.1 | python-dateutil |
| ==1.15.0 | six |
| ==4.54.1 | tqdm |
| ==0.17.2 | jedi |
| ==2.25.0 | requests |
| ==2.3.4 | spacy |
| ==1.26.2 | urllib3 |
| ==0.2.0.1 | lime |
| ==2.7.3 | pygments |
| ==1.1.1 | pywavelets |
| ==2.1.0 | threadpoolctl |
| ==0.7.4 | blis |
| ==3.1.1 | importlib-metadata |
| ==0.17.0 | joblib |
| ==1.3.1 | kiwisolver |
| ==3.3.3 | matplotlib |
| ==2.5 | networkx |
| ==8.0.1 | pillow |
| ==0.17.2 | scikit-image |
| ==0.23.2 | scikit-learn |
| ==3.4.0 | zipp |
| ==2020.12.4 | tifffile |
| ==5.0.5 | traitlets |
| ==4.8.0 | pexpect |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.5 | Python |
نحوه نصب
نصب پکیج whl argueview-0.2.1:
pip install argueview-0.2.1.whl
نصب پکیج tar.gz argueview-0.2.1:
pip install argueview-0.2.1.tar.gz