sorry, here is the XML
<operator name="Root" class="Process" expanded="yes">
<operator name="ExampleSource" class="ExampleSource">
<parameter key="attributes" value="C:\Programme\Rapid-I\RapidMiner-4.4\sinus"/>
<operator name="Normalization" class="Normalization">
<operator name="W-M5P" class="W-M5P">
<parameter key="keep_example_set" value="true"/>
<parameter key="U" value="true"/>
<parameter key="M" value="10.0"/>
<operator name="ModelApplier" class="ModelApplier">
What I get is a piecewise constant result, i.e. the leafes of the tree are: y = const
Only the last leaf gives a linear model: y = 3.2196 * x - 4.5545
If I had such a "really" linear model at all leafes of the tree, it would be ok, i.e. as
I would expect it.
There are no settings which can improve it, even if the tree could result in y = a*x+b
in each leaf, which should give a better prediction. So why does'nt M5P behave like
If I select the smoothed tree the results are even worse.
I hope I could make my "problem" more clear to you.
Maybe if you google for "stepwise regression tree HUANG" or go directly to http://www.landcover.org/pdf/ijrs24_p75.pdf
and there at page 77 (i.e. page 3 in the 16 pages document) you see what I
mean. If this SRT algorithm would become a part of RapidMiner I would
, even if I don't understand why M5P doesn't behave comparable.