Machine Learning in Python - Get the best possible feature-combination for a label
You could compute the representativeness of each feature to separate the classes via feature weighting. The most common method for feature selection (and therefore feature weighting) in Text Classification is chi^2. This measure will tell you which features are better. Based on this information you can analyse the specific values that are best for every case. I hope this helps.
Regards,
My Question is as follows:
I know a little bit about ML in Python (using NLTK), and it works ok so far. I can get predictions given certain features. But I want to know, is there a way, to display the best features to achieve a label? I mean the direct opposite of what I've been doing so far (put in all circumstances, and get a label for that)
I try to make my question clear via an example:
Let's say I have a database with Soccer games.
The Labels are e.g.  'Win', 'Loss', 'Draw'.
The Features are e.g. 'Windspeed', 'Rain or not', 'Daytime', 'Fouls committed' etc. 
Now I want to know: Under which circumstances will a Team achieve a Win, Loss or Draw? Basically I want to get back something like this:
Best conditions for Win: Windspeed=0, No Rain, Afternoon, Fouls=0 etc
Best conditions for Loss: ...
Is there a way to achieve this?