Index: docs/reference/rst/Orange.regression.rst
===================================================================
 docs/reference/rst/Orange.regression.rst (revision 10396)
+++ docs/reference/rst/Orange.regression.rst (revision 10537)
@@ 3,19 +3,10 @@
###########################
Orange uses the term `classification` to also denote the
regression. For instance, the dependent variable is called a `class
variable` even when it is continuous, and models are generally called
classifiers. A part of the reason is that classification and
regression rely on the same set of basic classes.

Please see the documentation on :doc:`Orange.classification` for
information on how to fit models in general.

Orange contains a number of regression models which are listed below.
+Orange implements a set of methods for regression modeling, that is,
+where the outcome  dependent variable is realvalued:
.. toctree::
:maxdepth: 1
 Orange.regression.mean
Orange.regression.linear
Orange.regression.lasso
@@ 23,4 +14,16 @@
Orange.regression.earth
Orange.regression.tree
+ Orange.regression.mean
+
+Notice that the dependent variable is in this documentation and in the
+implementation referred to as `class variable`. See also the documentation
+on :doc:`Orange.classification` for information on how to fit models
+and use them for prediction.
+
+*************************
+Base class for regression
+*************************
+
+All regression learners are inherited from `BaseRegressionLearner`.
.. automodule:: Orange.regression.base