This project forked from zwtforest/recommendersystems
程序以matlab语言编写，包括了Pearson相似度、UserCF、ItemCF、slope one算法、TopN推荐、MAE、RMSE、准确度、覆盖率等常用算法代码
License: MIT License
包括了Pearson相似度算法，基于用户的UserCF算法，基于物品的ItemCF算法，slope one算法，TopN推荐，MAE，RMSE，topN推荐准确度，覆盖率计算等常用算法
实验代码有些是两年前写的，编写有些不太规范，且个别程序时间复杂度上较高，先存在这上面，供以后自己有需要时能够方便温故、翻新。
由于推荐系统方面学术研究方面大多是是离线实验，且实验参数较多，每个学者改进的点不一样各固定参数可能与别的学者很少出现全部一直，所有完全复制一篇论文中的实验结果是极其困难的。且很多学者在文章中并没有交代，比如数据集中测试集和训练集的划分比例、实验次数、随机划分策略、目标用户和目标项目的占项目的比例、由于传统公式的缺陷性各种为出现无穷大和为1或者为0时的处理、近邻数量的设置、推荐列表长度的设置等等，所有的这些，有一个参数不一样，实验数据都会发生很大的变化。
那些曾经踩过的坑，待续……
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