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经典推荐算法实现
recsyspy's Introduction
经典推荐算法实现
- 基于scipy 稀疏矩阵构建数据模型
- 算法过程模块化,易于扩展
- 使用k折交叉验证测试算法
矩阵分解模型 |
RMSE |
MAE |
Baseline |
0.946 |
0.742 |
SVD |
0.931 |
0.731 |
SVDPlusPlus |
0.927 |
0.726 |
Explicit ALS |
1.199 |
0.903 |
Implicit ALS |
2.752 |
2.525 |
邻居模型 |
RMSE |
MAE |
Itemcf |
1.029 |
0.802 |
WeightedSlopOne |
1.043 |
0.835 |
- Yehuda Koren. Factorization meets the neighborhood: a multifaceted collaborative filtering model
- Matrix factorization techniques for recommender systems
- Advances in Collaborative Filtering
- Slope one predictors for online rating-based collaborative filtering
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