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.
|Depends:||R (≥ 3.1), methods|
|Imports:||Rcpp (≥ 0.11), Matrix, digest (≥ 0.6.8), magrittr (≥ 1.5)|
|LinkingTo:||Rcpp, digest (≥ 0.6.8), BH|
|Suggests:||RUnit, glmnet, knitr, xgboost, rmarkdown|
|Author:||Wush Wu [aut, cre], Michael Benesty [aut, ctb]|
|Maintainer:||Wush Wu <wush978 at gmail.com>|
|License:||GPL (≥ 3) | file LICENSE|
|CRAN checks:||FeatureHashing results|
Sentiment Analysis via FeatureHashing
|Windows binaries:||r-devel: FeatureHashing_0.9.1.1.zip, r-release: FeatureHashing_0.9.1.1.zip, r-oldrel: FeatureHashing_0.9.1.1.zip|
|OS X Mavericks binaries:||r-release: FeatureHashing_0.9.1.1.tgz, r-oldrel: FeatureHashing_0.9.1.1.tgz|
|Old sources:||FeatureHashing archive|
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