Data-driven Feature Selection Methods for Text Classification: an Empirical Evaluation

Autor: George D. C. Cavalcanti, Roberto H. W. Pinheiro, Rogerio C. P. Fragoso

Publikováno v: JUCS-Journal of Universal Computer Science 25(4): 334-360
Journal of Universal Computer Science, Vol 25, Iss 4, Pp 334-360 (2019)

Dimensionality reduction is a crucial task in text classification. The most adopted strategy is feature selection using filter methods. This approach presents a difficulty in determining the best size for the final feature vector. At Least One FeaTur

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2699e6195e72ac5f708c3b88334b6e6a
https://lib.jucs.org/article/22602/