Model without correlated attributes.

Hallo

I have different problems with my models
Usually are in practice always a lot of attributes are correlated each other.
Unfortunately, there is no such generator, which produces correlated attributes.
I can therefore show the present example, not directly. But the principle is the same.

But I would still find a way
a) I want to test all attributes combinations with each other. This may not be correlated !!
b) With the operator Feature Selection  I would like to decide how many variables are to be incorporated into the model. It is often not useful to have 20 variables in the model.
c) he will find the best model to me and write out the linear model as well.
d) Unfortunately, I did not get the forecast (prediction) for the model

But I have some problems with my model. Therefore I hope for your good ideas :-X

Many thanks for you opinion and help

Momo




My Modelkonstruction:


<operator name="Root" class="Process" expanded="yes">
    <operator name="Daten laden  und vorbereiten" class="OperatorChain" expanded="yes">
        <operator name="ExampleSetGenerator" class="ExampleSetGenerator">
            <parameter key="target_function" value="random"/>
        </operator>
        <operator name="RandomOptimizer" class="RandomOptimizer" expanded="yes">
            <parameter key="iterations" value="100"/>
            <operator name="RemoveCorrelatedFeatures (2)" class="RemoveCorrelatedFeatures">
                <parameter key="correlation" value="0.5"/>
                <parameter key="attribute_order" value="random"/>
            </operator>
            <operator name="CorrelationMatrix" class="CorrelationMatrix">
            </operator>
            <operator name="FeatureSelection" class="FeatureSelection" expanded="yes">
                <parameter key="plot_generations" value="100"/>
                <parameter key="keep_best" value="3"/>
                <parameter key="generations_without_improval" value="-1"/>
                <parameter key="maximum_number_of_generations" value="3"/>
                <operator name="XValidation" class="XValidation" expanded="yes">
                    <parameter key="create_complete_model" value="true"/>
                    <parameter key="local_random_seed" value="1"/>
                    <operator name="LinearRegression" class="LinearRegression">
                        <parameter key="feature_selection" value="none"/>
                    </operator>
                    <operator name="OperatorChain" class="OperatorChain" expanded="yes">
                        <operator name="ModelApplier" class="ModelApplier">
                            <list key="application_parameters">
                            </list>
                        </operator>
                        <operator name="RegressionPerformance" class="RegressionPerformance">
                            <parameter key="main_criterion" value="squared_correlation"/>
                            <parameter key="root_mean_squared_error" value="true"/>
                            <parameter key="squared_correlation" value="true"/>
                        </operator>
                    </operator>
                </operator>
            </operator>
        </operator>
        <operator name="ModelApplier (2)" class="ModelApplier">
            <parameter key="keep_model" value="true"/>
            <list key="application_parameters">
            </list>
        </operator>
    </operator>
</operator>