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
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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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