This is the data set I am working on, trying to predict
count (last column) :
datetime,season,holiday,workingday,weather,temp,atemp,humidity,windspeed,count 2011-01-01 00:00:00,1,0,0,1,9.84,14.395,81,0,16 2011-01-01 01:00:00,1,0,0,1,9.02,13.635,80,0,40 2011-01-01 02:00:00,1,0,0,1,9.02,13.635,80,0,32 ...
count distribution is an exponential decrease. I tried basic linear regression, but the result is bad. So, I guess there is an exponential correlation between
count and, at least, one of its predictors. I also guess there is linear correlation between
count and other predictors as well.
How to mix multiple linear and exponential regression ? I am working using the anaconda distribution of python, but i'd also like to understand the theory of the model if possible. Thanks !