CMF
Python implementation of Collective Matrix Factorization
Install / Use
/learn @VincentLiu3/CMFREADME
Collective Matrix Factorization
This is a python implementation of Collective Matrix Factorization using Newton's method.
Input Data Format
In this code, each relation is stored as a matrix in coordinate format. There are some examples in data/.
row,col,value
394,264,2
464,201,3
111,198,4
Quick Usage
$ python3 cmf.py --train data/ml-1m/train.txt --test data/ml-1m/test.txt --user data/ml-1m/user.txt --item data/ml-1m/item.txt --out ml-1m.txt --alphas '0.5-0.5-0.5' --link log_dense --k 8 --reg 0.1 --lr 0.1 --iter 50 --tol 0
You have to use python3 to run this code. Type python3 cmf.py --help for more details about the parameters.
Reference
* Singh, Ajit P., and Geoffrey J. Gordon. Relational learning via collective matrix factorization. Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2008.
Related Skills
node-connect
350.8kDiagnose OpenClaw node connection and pairing failures for Android, iOS, and macOS companion apps
frontend-design
110.4kCreate distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
openai-whisper-api
350.8kTranscribe audio via OpenAI Audio Transcriptions API (Whisper).
qqbot-media
350.8kQQBot 富媒体收发能力。使用 <qqmedia> 标签,系统根据文件扩展名自动识别类型(图片/语音/视频/文件)。
