PARTIAL LEAST SQUARES (PLS) LATENT VARIABLE MODELLING APPROACH FOR MEASURING DURATION OF ORTHODONTIC TREATMENT
نویسندگان
چکیده
منابع مشابه
Partial Least Squares Regression (PLS)
Number of latents The same number of factors will be extracted for PLS responses as for PLS factors. The researcher must specify how many latents to extract (in SPSS the default is 5). There is no one criterion for deciding how many latents to employ. Common alternatives are: 1. Cross-validating the model with increasing numbers of factors, then choosing the number with minimum prediction error...
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Pls regression is a recent technique that generalizes and combines features from principal component analysis and multiple regression. It is particularly useful when we need to predict a set of dependent variables from a (very) large set of independent variables (i.e., predictors). It originated in the social sciences (specifically economy, Herman Wold 1966) but became popular first in chemomet...
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Partial least squares (pls) regression (a.k.a projection on latent structures) is a recent technique that combines features from and generalizes principal component analysis (pca) and multiple linear regression. Its goal is to predict 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 ...
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ژورنال
عنوان ژورنال: MALAYSIAN JOURNAL OF COMPUTING
سال: 2020
ISSN: 2600-8238,2231-7473
DOI: 10.24191/mjoc.v5i1.7416