Kaggler – Python Package for Kaggler

This article was originally posted on Kaggle’s Avazu competition forum and reposted here with a few edits.

Here I’d like to share what I’ve put together for online learning as a Python package – named Kaggler.

You can install it with pip as follows:

$ pip install -U Kaggler

then, import algorithm classes as follows:

from kaggler.online_model import SGD, FTRL, FM, NN, NN_H2

Currently it supports 4 online learning algorithms – SGD, FTRL, FM, NN (1 or 2 ReLU hidden layers), and 1 batch learning algorithm – NN with L-BFGS AUC optimization.

It uses the liblinear style sparse input format – It is chosen so that the same input file can be used across other popular tools such as XGBoost, VWlibFM, SVMLight, etc.

Code and examples are available at https://github.com/jeongyoonlee/Kaggler, and package documentation is available at http://pythonhosted.org//Kaggler/.

Kaggler. Data Scientist.

Author: jeongyoonlee

Kaggler. Data Scientist.

Leave a Reply

Your email address will not be published. Required fields are marked *