| Name | chlearn JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | |
| Summary | 自己平时会使用的一些统计学和数学模型,目前有两个改进的朴素贝叶斯算法和一个TOPSIS |
| upload_time | 2023-08-07 04:48:29 |
| maintainer | |
| docs_url | None |
| author | Checkey01 |
| requires_python | |
| license | |
| keywords |
machine learning
python
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
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# 使用说明
自己平时会使用的一些统计学和数学模型,目前有两个改进的朴素贝叶斯算法和一个TOPSIS
GitHub: [https://github.com/CheckeyZerone/Checkey-Sklearn](https://github.com/CheckeyZerone/Checkey-Sklearn)
PyPI: [https://pypi.org/project/checkey-sklearn/](https://pypi.org/project/checkey-sklearn/)
## 版权声明
Checkey-Sklearn
Copyright (C) 2023 CheckeyZerone
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published
by the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
## 安装方法
```commandline
pip install chlearn
```
## 依赖的第三方模块包
```
numpy
pandas
scikit-learn
```
## 实现算法
- 朴素贝叶斯改进
- 熵权-TOPSIS模型
## 使用方法
```python
model = Model(*params)
model.fit(x_train[, y_train, params])
model.predict(x_test) # or model.transform(x_test)
```
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