pyFFM 0.0.2

Python implementation of Factorization Machines (+ Field Aware)

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*** early stage testing! ***

A python implementation of Factorization Machines / Field-aware Factorization Machines with a simple interface.

Installation:

pip install pyffm

Basic example:

import pandas as pd
from pyffm import PyFFM
training_params = {'epochs': 2, 'reg_lambda': 0.002}
pyffm = PyFFM(model="ffm", training_params=training_params)

file_path = 'path/to/csv/file'
df_in = pd.read_csv(file_path)
# Make sure your file has a label column, default name is 'click' but you can either rename it or pass in label
df_in.rename(columns={'label': 'click'}, inplace=True)

pyffm.train(df_in)
preds = pyffm.predict(df_in)

Sample data from: https://github.com/ycjuan/libffm

Created using the algorithm described in the original paper: https://www.csie.ntu.edu.tw/~cjlin/papers/ffm.pdf