I have the dataset which you can find here, containing many different characteristics of different houses, including their types of heating, or the number of adults and children living in the house. In total there are about 500 records. I want to use an algorithm, that can be trained using the dataset above, in order to be able to predict the electricity consumption of a house that is not in the set.
I have tried every possible machine learning algorithm (using weka) (linear regression, SVM etc) . However I had about 350 mean absolute error, which is not good. I tried to make my data to take values from 0 to 1, or to delete some characteristics. I did not managed to find some good results.
I also tried to use R tool, and I did not have good results either...
I would be very grateful, if someone could give me some advice, or if you could examine a little the dataset and run some algorithms on it. What type of preprocessing should I use, and what type of algorithm?
I have posted a similar question last month, but I did not get any useful answers.