%0 Thesis %1 noauthororeditor %A Ljungberg, Benjamin Fayyazuddin %D 2017 %K clustering downprojection lsa pca preethi %T Dimensionality reduction for bag-of-words models: PCA vs LSA %X We study a collection of texts stored as “bags of words” and implement two methods for reducing the dimension of the data. We compare how easy it is to perform authorship identification on the dimensionally-reduced data.

@mastersthesis{noauthororeditor, abstract = {We study a collection of texts stored as “bags of words” and implement two methods for reducing the dimension of the data. We compare how easy it is to perform authorship identification on the dimensionally-reduced data.}, added-at = {2019-09-02T16:41:45.000+0200}, author = {Ljungberg, Benjamin Fayyazuddin}, biburl = {https://www.bibsonomy.org/bibtex/205842080744cc8fbb88b4b1027028e8d/ghagerer}, institution = {Stanford}, interhash = {4a105fc0457839ba63658b08e6325d00}, intrahash = {05842080744cc8fbb88b4b1027028e8d}, keywords = {clustering downprojection lsa pca preethi}, timestamp = {2019-09-02T16:41:45.000+0200}, title = {Dimensionality reduction for bag-of-words models: PCA vs LSA}, year = 2017 }