luigif2000

https://analyticsindiamag.com/hands-on-guide-to-darts-a-python-tool-for-time-series-forecasting/

Sure dear Michael, I agree at all; about the problem: STEP 1) automl.fit(X_train=X[:-100], y_train=y[:-100], **settings, period=5, estimator_list=['lgbm', 'rf', 'xgboost', 'extra_tree', 'xgb_limitdepth'], seed=2, n_jobs=1, ) THE AUTOML FIT END REGURALLY WITHOUT...

as You can see i used X[:-100],y[:-100] with automl -> NO ERROR than i simply use X, y with clone -> ERROR ValueError: Found array with 0 sample(s) (shape=(0, 2420))...

HI dear, YES automl.fit(X, y, estimator_list=['lgbm', 'rf', 'xgboost', 'extra_tree', 'xgb_limitdepth'], period=5) WORK WITHOUT ERROR

Dear sonichi, the automl.fit(X,y,...) change the best final model......is not the same thing of michael kindly not working suggestion.... in other words: a) automl.fit(X[:-100],y[:-100]..... retrain with clone of the previous...

I need to: 1) train on X[:-100] 2) scoring on X[-100:] 3) train the best model found in point 2 on all X data (without changing hyperparameter) it's the finalize...

I’m very sorry I didn’t explain well, excuse me. Unfortunately the subject ML is borning now and we have to change our natural neuron to think Ml. Anyway: thanks so...

anyway i understand better the meaning of period parameters, (you remember i asked the meaning of period parameter at the beginning) thanks

Dear qingyun-wu, thanks so much for the kindly reply. I have realized many thinks thanks to you: 1) FLAML use (TRAIN +VALIDATION) for training 2) the lenght of VALIDATION is...

Please could You kindly reply also usefull information about categorical features in flaml?!? how to manage? how to pass? other...thanks again luigi