When does it make sense to try to learn a Mixture model from a data set? (Multiple answers with negative points) A. When the data set is multimodal, so it is unlikely that a simple distribution will fit the data well. B. When we want to describe a complex distribution by combining simpler component distributions. C. When there are no clear indications or theoretical justifications for the presence of multiple subpopulations. D. When we have ovrelaping clusters. E. When your data can be adequately represented by a simple, well-understood distribution. F. When there is a clear linear relationship between input data variables