Creates a Model Matrix via Feature Hashing With a Formula
Interface
as.person(c( "Wush Wu <wush978@gmail.com> [aut, cre]"))
Feature hashing, also called as the hashing trick, is a method to
transform features to vector. 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). The hashing algorithm is the murmurhash3
from the digest package. Please see the README.md for more information.

Creates a Model Matrix via Feature Hashing with a Formula
Interface
c(
person("Wush", "Wu", email = "wush978@gmail.com", role = c("aut", "cre")),
person("Michael", "Benesty", email = "michael@benesty.fr", role = c("aut", "ctb")))
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).
The hashing algorithm is the murmurhash3 from the digest package.
Please see the README in https://github.com/wush978/FeatureHashing for more information.
RUnit, glmnet, knitr, xgboost, rmarkdown
Wush Wu [aut, cre],
Michael Benesty [aut, ctb]

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.