Open Mushahid2521 opened 2 years ago
Hi @Mushahid2521
Yes, this is possible! :)
If you have another dataset without label information, you can still create a SIAMCAT
object without a label. It will throw a warning, but it will work. Then, you can follow the Holdout testing vignette to predict on new samples with a trained model.
Cheers, Jakob
Thanks a lot. It worked.
Sorry. I am experiencing a new issue. My holdout feature table doesn't contain all the OTUs that are present in the training feature table. I get the following error message while performing normalize.features according to Holdout testing vignette.
Error in normalize.features(sc.obj.test, norm.param = norm_params(sc.obj), :
all(norm.param$retained.feat %in% row.names(feat)) is not TRUE
Is there a way to predict the new sample otutable? I don't have any metadata for those samples.
TIA