Open-source alternatives to Tffm

Factorization machines in python

fastFM: A Library for Factorization Machines

Relevance Vector Machine implementation using the scikit-learn API.

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

ThunderSVM: A Fast SVM Library on GPUs and CPUs