Earth Learner
Signal Predictor
sends data only if the input signal
Data
is present.
This widget constructs a Earth learning algorithm (an implementation of the
MARS - Multivariate Adaptive Regression Splines). As all widgets for
classification and regression, this widget provides a learner and
classifier/regressor on the output. Learner is a learning algorithm with
settings as specified by the user. It can be fed into widgets for testing
learners, for instance Test Learners
.
Learner can be given a name under which it will appear in, say, Test Learners
.
The default name is "Earth Learner".
The Max. term degree
parameter specifies the degree of the terms induced in
the forward pass. For instance, if set to 1
the resulting model will contain
only linear terms.
The Max. terms
specifies how many terms can be induces in the forward pass.
A special value Automatic
instructs the learner to set the limit automatically
based on the dimensionality of the data
(min(200, max(20, 2 * NumberOfAttributes)) + 1
).
The Knot penalty
is used in the pruning pass (hinge function penalty for
the GCV calculation)
After changing one or more settings, you need to push Apply, which will put the new learner on the output and, if the training examples are given, construct a new predictor and output it as well.
Lets use the learner to train a model on a data subset and test it on unseen instances.