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CMF

Python implementation of Collective Matrix Factorization

Install / Use

/learn @VincentLiu3/CMF
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

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

View on GitHub
GitHub Stars19
CategoryDevelopment
Updated2mo ago
Forks6

Languages

Python

Security Score

80/100

Audited on Jan 13, 2026

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