alno/batch-learn

Batch Learn

Batch-Learn is an implementation of ML algorithms which may be applied to on-disk data batch-by-batch, without loading full dataset to memory.

Algorithms included:

• FFM
• NN / MLP

It's extracted from the code written during Outbrain Click Prediction competition on Kaggle and now is undergoing some rewrite and refactoring.

Installation

Batch-learn uses CMake as a build tool and depends on following libraries:

• boost-program-options
• boost-iostreams

To compile code you need to install boost libraries and then call:

mkdir build
cd build
cmake ..
make

Usage

First, you need to convert to batch-learn format:

batch-learn convert -f ffm -b 24  ffm_dataset.txt -O bl_dataset

To train ffm model and make predictions on test dataset:

batch-learn ffm --train tr1 --test te1 --pred pred.txt

You also may specify validation dataset:

batch-learn ffm --train tr1 --test te1 --val va1 --pred pred.txt

To get list of available commands just run:

batch-learn help

To get help about some specific command:

batch-learn help ffm