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.
|Depends:||R (≥ 3.1), methods|
|Imports:||Rcpp (≥ 0.11), Matrix, digest (≥ 0.6.8), magrittr (≥ 1.5)|
|LinkingTo:||Rcpp, digest (≥ 0.6.8), BH (≥ 1.54.0-1)|
|Suggests:||RUnit, glmnet, knitr, xgboost, rmarkdown, pROC|
|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_0.9.1.5.zip, r-release: FeatureHashing_0.9.1.5.zip, r-oldrel: FeatureHashing_0.9.1.5.zip|
|macOS binaries:||r-release (arm64): FeatureHashing_0.9.1.5.tgz, r-oldrel (arm64): FeatureHashing_0.9.1.5.tgz, r-release (x86_64): FeatureHashing_0.9.1.5.tgz, r-oldrel (x86_64): FeatureHashing_0.9.1.5.tgz|
|Old sources:||FeatureHashing archive|
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