the Dataset class does not contain the data but just the description of the attributes. You don't need to load the training data but your test data should have similar attributes to the training data, thus your test Dataset object should be similar to your train Dataset.
You can take a look at the TestForest example and especially the sequential() method to see how to use the classification. On Tue, Aug 14, 2012 at 1:11 AM, Yuhan Zhang <[email protected]> wrote: > some typo in the last email: > name of the method is decisionForest.classify(dataset, random, Instance) > > if a dataset other than training dataset is given, it will result > IllegalArgumentException:values not found for attribute 1. > > need some help here. > > Yuhan > > On Mon, Aug 13, 2012 at 5:03 PM, Yuhan Zhang <[email protected]> wrote: > > > Hi all, > > > > I'm trying to train a decision forest, save it to file, and use it > latter. > > I have managed to write a trained decision forest to file using > > "DecisionForest.write( dataOutPut ) "; > > > > but when I load a saved decision tree from file to classify, I realized > > the the method > > DecisionForest.classifier(Dataset, random, Instance) is expecting the > > original training Dataset. > > > > Is there a way to avoid loading the training Dataset? It is kind large, > > and I'd like to avoid loading it. > > > > > > Thank you > > > > Yuhan > > > > > -- > Yuhan Zhang > Senior Software Engineer > OneScreen Inc. > [email protected] <[email protected]> > www.onescreen.com > (949) 525-4825 Ext: 177 > > > The information contained in this e-mail is for the exclusive use of the > intended recipient(s) and may be confidential, proprietary, and/or legally > privileged. Inadvertent disclosure of this message does not constitute a > waiver of any privilege. If you receive this message in error, please do > not directly or indirectly print, copy, retransmit, disseminate, or > otherwise use the information. In addition, please delete this e-mail and > all copies and notify the sender. >
