I have monthly price data for tomatoes for the last 9 yrs for a particular town and I'm looking to predict the prices of tomatoes 6 months into the future.
I had considered using Linear Regression in Tensorflow (something I learnt about a week ago), because there is a direct relationship between price and rainfall for the location in question. That is, high rainfall means a supply glut and a price drop, low rainfall means scarcity and price hikes.
However I've found that I can't get accurate weather forecasts for 6 months into the future and have to use some other way other than Linear Regression to predict future tomato prices.
What is the best way to do this?