Time series forecasting (Gradient Boosting)
I am trying to predict a short time, stationary series (the length of the series is 40 values). So far, I have been able to do this using statistical methods, the results of which are relatively satisfactory to me. In order to explore other forecasting methods, I am considering the Boosting Regression (GradientBoostingRegressor, XGBRegressor,) and SVR classes. Forecasts cannot be built, the models give one value for all x_train. I can’t figure out what I’m doing wrong. I doubt that I am preparing the data for the models correctly.
Dense Time Series Data
Picture of my plot
Picture of my code
Demand forecast in Supply Chain – Multivariate time series forcasting
I have a weekly time series data set as shown here :
Ljung-Box returns lb_pvalue
I’m currently reading a time series book and trying to code along with the book but the output of my ljung-box test and the book is different. The book outputs shows the p-value of each lags while mine shows the output of lb_pvalue. Why does my output returns lb_pvalue instead of output of the p-values of each lag? Is there something I did wrong?