mlfactor.github.io
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Features in the data
In 5.1.3 Illustration, I try to use your code and data to compute Lasso as you did in your book:
library(glmnet) y_penalized <- data_ml$R1M_Usd # Dependent variable x_penalized <- data_ml %>% # Predictors dplyr::select(all_of(features)) %>% as.matrix() fit_lasso <- glmnet(x_penalized, y_penalized, alpha = 1) # Model alpha = 1: LASSO
in dplyr::select(all_of(features)) %>% as.matrix(), since there is no "features" in your data, I cannot repeate your compution. Is the data in github is not the one you used in your book?
Thanks and regards, Mike
Dear Mike,
sorry for the inconvenience. The set of features is defined in Chapter 2 as: features <- colnames(data_ml[3:95])
With this it should work. Best,
Guillaule
Dear Guillaule,
Many thanks for your quick response! It really solve my problem.
With Best Regards, Mike