pls

问题 I'm using tidymodels to fit a PLS model but I'm struggling to find the PLS variable importance scores or coefficients. This is what I've tried so far; the example data is from AppliedPredictiveModeling package. Modeling fitting data(ChemicalManufacturingProcess) split <- ChemicalManufacturingProcess %>% initial_split(prop = 0.7) train <- training(split) test <- testing(split) tidy_rec <- recipe(Yield ~ ., data = train) %>% step_knnimpute(all_predictors()) %>% step_BoxCox(all_predictors()) %>%

问题 I am trying to perform a PLSRegression using the code from sklearn and I want to keep with those components that explain some level of variance, like in PCA. Is there a way to know how much variance is explained by each component in PLS 回答1: I also have the same requirement of calculating each components' explained variance. I am new for PLS and not a native English speaker, please just take my solution for your reference. Backgroud: If you choose the 'deflation_mode' as "regression", which