On Tue, Oct 6, 2009 at 1:41 PM, chung <chvng at mail.ntua.gr> wrote:

> Dear Nina, Christoph, All,
>
> Datasets with missing values are valid, however we have to bear in mind
> some density/sparsity criteria at least for the time. Its absolutely
> impossible to train a model (even a "bad" one), using the following
> "diagonal" dataset:
>

But wouldn't the model development stage involve data cleaning to remove (or
impute) missing values? And if there isn't sufficient information content,
why would one build a model in the first place?

-- 
Rajarshi Guha
NIH Chemical Genomics Center