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Data Model
==========

The Data Model component of the |full_name| (|short_name|)
provides classes for model representation. The
model mimics the actual data and represents it in a compact way so
that you can use the library when the actual data is missing,
incomplete, noisy or unavailable.

There are two categories of models in the library: Regression models
and Classification models. Regression models are used to predict the
values of dependent variables (responses) by observing independent
variables. Classification models are used to predict to which
sub-population (class) a given observation belongs.

A set of parameters characterizes each model. |short_name| model
classes provide interfaces to access these parameters. It also
provides the corresponding classes to train models, that is, to
estimate model parameters using training data sets. As soon as a
model is trained, it can be used for prediction and cross-validation.
For this purpose, the library provides the corresponding prediction
classes.