文件名称：recommeder-for-onlinedocs:基于内容相似度，协同过滤以及逻辑回归的推荐系统
文件大小：2.85MB
文件格式：ZIP
更新时间：2024-04-07 07:50:17
JavaScript
recommeder-for-onlinedocs:基于内容相似度，协同过滤以及逻辑回归的推荐系统
【文件预览】：
recommeder-for-onlinedocs-master
----source()
--------conf.py(2KB)
--------基于Content-Base、Collaborative Filtering及Logistic Regression算法的推荐系统Demo实现.md(17KB)
--------index.rst(548B)
----make.bat(764B)
----CF_Process()
--------3th_CF2-2_0_User2Item_ScoreNormalize_cfTrain2.py(2KB)
--------3th_CF2-2_1_User[Sorted]2Item_ScoreCal_cfTrain3.py(880B)
--------2rd_CF2-1_Item[Sorted]2User_ScoreCal_cfTrain1.py(856B)
--------4th_CF2-3_Item2Item_ScoreCal_cfResult.py(3KB)
--------1st_CF1_User2Item_ScoreCal_cfTrain.py(2KB)
--------test_for _CF.py(769B)
--------5th_CF3_Item2[Item-Score]_groupCal_cfReclis.py(1KB)
--------6th_cfReclist_to_RedisSQL.py(259B)
----CB_Process()
--------test_for_CB.py(160B)
--------1st_data_processing_mergeBase.py(1KB)
--------2nd_CB1_token2Item_ScoreCal_cbTrain.py(3KB)
--------3rd_CB2-1_token2Item_ScoreCal_cbTrain1.py(883B)
--------5th_CB3_Item2[Item-Score]_groupCal_cbReclis.py(2KB)
--------6th_cbReclist_to_RedisSQL.py(371B)
--------4th_CB2-2_Item2Item_ScoreCal_cbResult.py(4KB)
----Demo()
--------app.py(252B)
--------main.py(6KB)
--------testing.py(211B)
--------__pycache__()
----.idea()
--------misc.xml(288B)
--------other.xml(186B)
--------workspace.xml(40KB)
--------music-top-recomend.iml(453B)
--------encodings.xml(337B)
--------modules.xml(288B)
----Modelling_LogisticRegression()
--------test.py(127B)
--------2rd_Modelling.py(3KB)
--------1st_data_prepare.py(6KB)
----build()
--------html()
--------doctrees()
----Makefile(638B)