A theory of learning from different domains

Shai Ben-David; John Blitzer; Koby Crammer; Alex Kulesza; Fernando Pereira; Jennifer Wortman Vaughan

Năm xuất bản2009

Nguồn học thuậtMachine Learning

Định danhDOI 10.1007/s10994-009-5152-4

TRÍCH DẪN ĐỀ XUẤTAPA 7

Shai Ben-David; John Blitzer; Koby Crammer; Alex Kulesza; Fernando Pereira; Jennifer Wortman Vaughan (2009). A theory of learning from different domains. Machine Learning, 79(1-2), 151-175. https://doi.org/10.1007/s10994-009-5152-4

Thông tin thư mục

Nguồn/Tạp chí: Machine Learning
Tập: 79
Số: 1-2
Trang: 151-175
Nhà xuất bản: Springer Science+Business Media
DOI: 10.1007/s10994-009-5152-4 ↗

Từ khóa

Classifier (UML); Computer science; Weighting; Discriminative model; Artificial intelligence; Bounding overwatch; Pattern recognition (psychology); Bayes error rate; Labeled data; Machine learning; Test data; Quadratic classifier; Divergence (linguistics); Algorithm; Bayes classifier; Support vector machine; Naive Bayes classifier