A Pair-wise Learning to Rank Model using Random Forest

Setup Environment

First you need to install dependencies as follows:

• Create a virtualenv:

$ virtualenv venv
$ source venv/bin/activate

• Run:

$ pip install -r requirements.txt

Usage

For training:

$ python rf-ranker.py train path_to_train_data_file.tsv

For testing:

$ python rf-ranker.py test path_to_test_data_file.tsv"

File schema

Files containing data points must have the following schema: Each instance must have two rows; a header row and a content row.

Example:

object_id \t data_point_id \t label \t feature_1 \t ..... \t feature_n

train_object_1 \t id_1 \t 0.4 \t 1.0 \t .... \t 0.5

For testing, "label" column is dropped.

Code

The code is based on the following paper: More Accurate Question Answering on Freebase [pdf] Hannah Bast, Elmar Haussmann

You can find the original code at: https://github.com/elmar_haussmann/aqqu

However, we re-implemented the code for easier accessibility.