ipinyou

ipinyou.test

ipinyou.train

This is a sample from the iPinYou Real-Time Bidding dataset.
The data.frame named <code>ipinyou.train</code> is a sample from the data of 2013-10-19 and
the data.frame named <code>ipinyou.test</code> is a sample from the data of 2013-10-20.

Feature hashing, also called as the hashing trick, is a method to transform
features of a instance to a vector. Thus, it is a method to transform a real dataset to a matrix.
Without looking up the indices in an associative array,
it applies a hash function to the features and uses their hash values as indices directly.
The method of feature hashing in this package was proposed in Weinberger et al. (2009) <arXiv:0902.2206>.
The hashing algorithm is the murmurhash3 from the 'digest' package.
Please see the README in <https://github.com/wush978/FeatureHashing> for more information.

Wush Wu

FeatureHashing

Creates a Model Matrix via Feature Hashing with a Formula
Interface

Michael Benesty

ipinyou function

The column name of the data is the description of the data in Zhang, Yuan, Wang, et al. (2014).
Most of the columns should be clearly described by their column names.
For the details of the dataset, please read the Zhang, Yuan, Wang, et al. (2014).<code>BidID</code>, the id of the RTB which is the unique identifier of the events.<code>Adid</code>, the advertiser id.<code>UserTag</code>, the user tags (segments) in iPinYou's proprietary audience database.
This is also a real example of the concatenated feature.

ipinyou: iPinYou Real-Time Bidding Dataset for Computational Advertising Research

Description

Usage

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References