My hierarchical data are about sell numbers of 3 hot drinks and 3 cold drinks each month.
Generally, cluster them into two group which one contain hot and another contains cold is better. But I don't want to cluster. When I study about sklearn.linear_model, I found they can only predict one trend for both hot and cold pattern. The trend of hot and cold is the same. But that make sense because it's "linear" model which suitable for linear separable data. Now, I want to predict different trend for hot and cold drink with only one model. If I have many features as I can, is there any model able to predict multiple patterns from hierarchical data? PS: under the condition that has no noise, data only conatin each trend of each kind of drink. thx
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