About the LinearRegression operator

Legacy User

Hi,

I am a new user of rapidminer. I tried to use the LinearRegression operator and I ran with my dataset. But in the end I did not get an equation. I am currently trying to train a model.

My process are as follows:

Root

 >CSV Example Source

 >Attribute Filter

 >RemoveUselessAttributes

 >Genetic Algorithm

   >>Operator Chain

      >>>X-Validation

            >>>>LinearRegression

            >>>>OperatorChain(2)

                     >>>>>>ModelApplier

                     >>>>>>RegressionPerformance

            >>>>ProcessLog

 >CSV Example Set Writer


Thanks!

haddock

Hi there,

The optimisation produces a parameter set for the learning operator and anything else you tweak, rather than a model. To keep it simple the process is like this.

1. Generate a parameter set - you've done that.

2. Apply that set using the parameter setter operator. You'll need to map between the optimised parameters and the ones you will use. So if I had optimised an SVM and some Validation settings I would have this sort of mapping.

<operator name="ParameterSetter" class="ParameterSetter" activated="no">
            <list key="name_map">
              <parameter key="NNValidation" value="NNValidation (2)"/>
              <parameter key="LIbSVMLearner" value="LibSVMLearner (2)"/>
            </list>
        </operator>

3. Run the same learner on an appropriate dataset ( careful here ). That will produce the optimised model which has this sort of form.

31.736 * a1 + 42.948 * a2 + 23.773 * a3 + 3.706 * a4 - 4.184 * a5 - 304.228

Where a1 etc. are the attribute names.

With RM a big skill is to keep track of the inputs and ouputs of the operators, because sometimes it is not what you think!