I have a set of data from the last 10 days, updated every 15 minutes, which state the temperature and humidity in a closed area (no external influences), for example a greenhouse, in the format: temperature_value, humidity_value, date(dd-mm-yyyy hh:mm:ss).
Can anyone point me to some useful short term prediction algorithms that I can use to make prediction over the following days for these values? The results will be shown every 15 minutes in the future, just like the training set is.
Basically, what I want most is to compare those algorithms and to see which one was more precise, once the time passes.
From searching over the internet, I have found some algorithms like "support vector machines", "linear regression", "random forests", but I am not sure these will help me in my particular situation, as, from what I understood, they tend to make predictions too, but on another level (for example, to predict if a mail if spam based on it's characteristics).
Thank you for your kind answers!