luigif2000

for example, verstack has fit(X,y) to "Execute LGBM model hyperparameters tuning " and has fti_optimized(X,y) to "Train model with tuned params on whole train data".............. waiting Your help....

ok thank's so much.... you are very welcome best regards luigi Il giorno mar 2 ago 2022 alle ore 23:14 Qingyun Wu ***@***.***> ha scritto: > Hi @luigif2000 , >...

sure, i did...no more help for now...have a nice day thanks again luigi Il giorno ven 5 ago 2022 alle ore 13:58 Qingyun Wu ***@***.***> ha scritto: > You are...

https://towardsdatascience.com/the-complete-guide-to-time-series-analysis-and-forecasting-70d476b

Hi and thanks for the kindly reply. I'm referring to what is magically explain in the following document: https://towardsdatascience.com/the-complete-guide-to-time-series-forecasting-using-sklearn-pandas-and-numpy-7694c90e45c1 Now I ask You: how to forecast a time series 5days(for...

Dear thanks for your kindly reply, that's very kind of You! You true but my question is regarding the test data that at the end is non trained or fitted,...

Dear michael and sonichi, thanks for your replies! 1) unfotunatelly the great michael suggestion doesn't work: no way. Various error encountered..... The big problems remain to understand the theory behind...

Hope to simplify in a phrase: the best final model (the production model) should know all, ALL the data!? Is it right?

Dear sonichi another issue: i have always thought that a multivariate time series forecasting model should take care about the feature using lagged label? In this way a need to...

https://github.com/pycaret/pycaret/issues/975