Index: Orange/multitarget/tree.py
===================================================================
--- Orange/multitarget/tree.py (revision 10092)
+++ Orange/multitarget/tree.py (revision 10335)
@@ -62,12 +62,22 @@
class MultitargetVariance(Orange.feature.scoring.Score):
"""
- A multi-target score that ranks features based on the variance of the
- subsets. A weighted distance can be used to compute the variance.
+ A multi-target score that ranks features based on the average class
+ variance of the subsets.
+
+ To compute it, a prototype has to be defined for each subset. Here, it
+ is just the mean vector of class variables. Then the sum of squared
+ distances to the prototypes is computed in each subset. The final score
+ is obtained as the average of subset variances (weighted, to account for
+ subset sizes).
+
+ Weights can be passed to the constructor to normalize classes with values
+ of different magnitudes or to increase the importance of some classes. In
+ this case, class values are first scaled according to the given weights.
"""
def __init__(self, weights=None):
"""
- :param weights: Weights of the features used when computing distances.
- If None, all weights are set to 1.
+ :param weights: Weights of the class variables used when computing
+ distances. If None, all weights are set to 1.
:type weigts: list
"""