fengyang95 / Tiny_ml
numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法
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tinyml
利用numpy实现的一些周志华《机器学习》（西瓜书）一书及 斯坦福cs229课程中的算法，宜配合西瓜书和cs229课件食用。并选择性实现了一些经典算法的简易版本， 如 按照陈天奇的slides实现的XGBRegressor。
已经实现的算法
- 线性模型
- LinearRegression 线性回归闭式解推导
- LogisticRegression 逻辑回归相关推导
- SGDRegressor
- LocallyWeightedLinearRegression
- 判别分析
- LDA
- GDA
- 决策回归树
- DecisionTreeClassifier
- DecisionTreeRegressor
- 支持向量机
- SVC
- 贝叶斯
- NaiveBayesClassifier
- 聚类算法
- KMeans
- LVQ
- GaussianMixture
- DBSCAN
- AGNES
- 降维算法
- MDS
- PCA
- KernelPCA
- LLE
- Isomap
- 集成学习
- AdaBoostClassifier
- GradientBoostingRegressor
- RandomForestRegressor
- XGBRegressor
- 特征选择
- ReliefFeatureSelection
和sklearn实现的比较
- 回归算法结果 代码
| Algorithm vs. RMSE | sklearn-boston | |
| tinyml | sklearn | |
| LinearRegression | 27.196 | 27.196 |
| SGDRegressor | 27.246 | 27.231 |
| DecisionTreeRegressor | 21.887 | 21.761 |
| RandomForestRegressor | 21.142 | 21.142 |
| GradientBoostRegressor | 16.778 | 16.106 |
| XGBRegressor | 20.149 | 15.7 |
- 分类算法结果 代码
| Algorithm vs. RMSE | sklearn-breast_cancer | |
| tinyml | sklearn | |
| NaiveBayes | 90.64% | 90.64% |
| LogisticRegression | 92.98% | 92.98% |
| LDA | 94.15% | 92.40% |
| GDA | 92.40% | 93.57% |
| SVC | 86.55% | 92.98% |
| AdaboostClassifier | 92.40% | 92.40% |
- 聚类算法比较 代码
- KMeans
- DBSCAN
- GMM
- AGNES
- 降维算法比较 代码
- PCA
- KernalPCA
- LLE
- MDS
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