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Estimation of predictive performance for test data in applicability domains using y‐randomization
Author(s) -
Kaneko Hiromasa
Publication year - 2019
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.3171
Subject(s) - python (programming language) , measure (data warehouse) , regression , regression analysis , linear regression , statistics , matlab , computer science , correlation , mathematics , data mining , property (philosophy) , algorithm , philosophy , geometry , epistemology , operating system
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