I'm currently doing a time-series forecasting project for the agriculture sector. I've been doing well so far, but now I'm stuck. I would like to have a 14-day forecast horizon, but here is where the problems start: I'm shifting prediction column by (-14) from target to see if there is a trend, but the error just explodes to 35% MAPE (mean absolute percentage error).

I recently tried to make predictions through LinearRegression and RandomForestRegressor, but the error is almost the same.

Any idea of what I can do to improve my model or where I should look instead of trying just a bunch of random things? (As you may see, I'm not too experienced, just gaining knowledge.).

Below in the image, I get a very clear seasonal pattern (for a two-week period), and I think it would be wise to focus on my approach here.

What do you think?

I'm currently doing a time-series forecasting project for the agriculture sector. Basically i'm trying to make predictions about fruit future prices. I've been doing well so far, but now I'm stuck. I would like to have a 14-day forecast horizon with a margin error of 15 cents in our price, but here is where the problems start: I'm shifting prediction column by (-14) from target to see if there is a trend, but the error just explodes to 0.59€ per kilo.

I recently tried to make predictions through LinearRegression and RandomForestRegressor, but the error is almost the same.

Any idea of what I can do to improve my model or where I should look instead of trying just a bunch of random things? (As you may see, I'm not too experienced, just gaining knowledge.).

Below in the image, I get a very clear seasonal pattern (for a two-week period), and I think it would be wise to focus on my approach here.

What do you think?