This is a known problem that should be fixed in trunk. While you are at it, the LogisticModelParameters approach may not be as useful as the ModelSerializer approach.
Here is a comparison of pros and cons: LogisticModelParameters + incorporates lots of CSV parsing info + serializes the whole lot including model and data representation + somewhat simpler to use + matches chapter 13 of MiA examples -- uses json to serialize model - pretty much assumes CSV input by implication - has a bug in many recent versions ModelSerializer ++ allows binary serialization + makes no assumptions about how feature vectors are encoded - requires that you make your own arrangements for vector encoding The bit about binary serialization is (for me) a real show-stopper for LMP for big models. Almost as important is the issue about vector encoding since real Mahout applications tend to have large sparse text-like input variables. On Wed, Jan 26, 2011 at 9:44 AM, Claudia Grieco <[email protected]>wrote: > What do you think can be the problem? >
