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display-advertising-challenge

(★ 130)

Criteo/Kaggle Competition of CTR prediction

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Download Latest Version (.zip)

- .gitignore
- .gitignore
- pom.xml
- shuffle.py
- submit.py
- vw_run.py
- .gitignore
.gitignore
LICENSE
README.md
run.sh

# Installation Guide

1. Get the code

git clone https://github.com/songgc/display-advertising-challenge

Downloads the entire project code from GitHub to your computer.

cd display-advertising-challenge

Moves into the project folder you just downloaded.

2. Maven (Java)

Medium Recommended

Prerequisites

Git Needed to download the project code from GitHub.
JDK (Java) Required to build and run Java projects.
Maven The build tool used for the mvn command.

$ mvn package # or mvn install

Installs dependencies and builds the project using Maven.

✅ A BUILD SUCCESS message means it worked. The output is created under target/.

Pulled directly from this repo's README.

// repository documentation

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Display Advertising Challenge
=============================

Description
-----------
This is the code was written for the [Kaggle Criteo Competition of CTR prediction](https://www.kaggle.com/c/criteo-display-ad-challenge).

Since the data are highly sparse, the basic methodology is to use logistic regression with appropriate quadratic/polynomial feature generation and regularization to make sophisticated and over-fitting-tractable models. [Vowpal Wabbit](https://github.com/JohnLangford/vowpal_wabbit) is the major machine learning software used for this project. Since the data size is challenging in terms of my personal workstation (a single quad-core CPU), the techniques of feature selection and model training are selected based on the trade off between performance and CPU/RAM resource limit.

Dependencies and requirements
-----------------------------
Please note that the code was written for my personal learning and practice in new features of Java 8 and Python 3.4 in Ubuntu 14.04. The code cannot be run in early versions of these two languages or other OSs. Compatibility is not considered here.

* Java 8
* Python 3.4
* Maven 3
* Redis 2.8
* Pandas 0.14
* Vowpal Wabbit 7.7
* Java-based open source projects: (Maven will install them automatically)
  - guava 17.0
  - jedis 2.5.1
  - commons-lang3 3.3.2

How to run
----------
- Copy train and test data file (train.csv, test.csv) to data folder
- Compile the Java code by
```
$ cd display-ad-java
$ mvn package # or mvn install
```
- Make sure a redis instance running at localhost:6379
- Set the path of binary vw (VW_BIN) in run.sh, such as 
```
export VW_BIN=/path/to/vw/binary
```
- Finally, 
```
$ cd work
$ ../run.sh
```