TY - CHAP
T1 - Design of experiments in computational linguistics
AU - Sidorov, Grigori
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - As we mentioned earlier in the book, in the automatic analysis of natural language (natural language processing, NLP) and in computational linguistics, machine learning methods are becoming more and more popular. Applying these methods increasingly gives better results. In this chapter, we describe the design of experiments in computational lingusitics: problem – corpus – gold standard – feature selection – dimensionality reduction – classification – evaluation (k-fold cross validation).
AB - As we mentioned earlier in the book, in the automatic analysis of natural language (natural language processing, NLP) and in computational linguistics, machine learning methods are becoming more and more popular. Applying these methods increasingly gives better results. In this chapter, we describe the design of experiments in computational lingusitics: problem – corpus – gold standard – feature selection – dimensionality reduction – classification – evaluation (k-fold cross validation).
UR - http://www.scopus.com/inward/record.url?scp=85064595592&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-14771-6_5
DO - 10.1007/978-3-030-14771-6_5
M3 - Capítulo
AN - SCOPUS:85064595592
T3 - SpringerBriefs in Computer Science
SP - 21
EP - 26
BT - SpringerBriefs in Computer Science
PB - Springer
ER -