Why Is The Partial Least Square Important For Tourism Studies
نویسندگان
چکیده
منابع مشابه
Partial least squares methods: partial least squares correlation and partial least square regression.
Partial least square (PLS) methods (also sometimes called projection to latent structures) relate the information present in two data tables that collect measurements on the same set of observations. PLS methods proceed by deriving latent variables which are (optimal) linear combinations of the variables of a data table. When the goal is to find the shared information between two tables, the ap...
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PLS regression is a recent technique that generalizes and combines features from principal component analysis and multiple regression. Its goal is to predict or analyze a set of dependent variables from a set of independent variables or predictors. This prediction is achieved by extracting from the predictors a set of orthogonal factors called latent variables which have the best predictive pow...
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In this study, the direct determination of cefixime as an anti-bacterial agent, in pharmaceutical formulations, urine and human blood plasma was conducted based on spectrophotometric measurements using parallel factor analysis (PARAFAC) and partial least squares (PLS). The calibration set was composed of fourteen solutions in the range of 0.50- 9.00 µg mL-1. PLS models were calculated at each p...
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ژورنال
عنوان ژورنال: International Journal of Tourism, Heritage and Recreation Sport
سال: 2019
ISSN: 2685-3663,2686-5092
DOI: 10.24036/ijthrs.v1i2.27