I have a problem that can be seen as the inverse of a classification problem. I don't need to classify points, but to explain the differences (if any) between points in different, pre-specified classes.
Let's say there are two states of the world: summer and non-summer. During summer, the sales of apples are down vs non-summer.
The hypothesis is that some people buy apples year-round and some stop or drastically reduce their apples consumption in summer. And/or some varieties of apples are way down in the summer whereas some others are relatively robust to the summer effect.
I have a dataset with apple features (varieties, etc) and their sales and buyers, and a dataset with features about the buyers.
What is a good technique or model that can tell me which features (about apples and/or buyers) do a good job of discriminating summer-sensitive apples/buyers from non summer-sensitive apples/buyers?