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 1 
 on: Today at 05:58:33 PM 
Started by Daniela - Last post by Marius
Hi Daniela,

Birgit told me that you are using the decay.txt from the zip file. That file contains only 30 data points, which by far not enough to derive the formula that you posted. If you plot y vs. x you see that this looks rather linear with a coefficient of -3 (visual estimation :-) ), so RapidMiner does not perform that bad Smiley
Does R work better on the same data set?
Do you really have 300 entries in your data? I only see 30 with a step size of 1.

Best regards,
Marius

 2 
 on: Today at 03:05:54 PM 
Started by veve - Last post by Marco Boeck
Hi,

have a look at the following example process. It should work straight away.

Code:
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="6.0.009">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="6.0.009" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="retrieve" compatibility="6.0.009" expanded="true" height="60" name="Retrieve Golf" width="90" x="45" y="75">
        <parameter key="repository_entry" value="//Samples/data/Golf"/>
      </operator>
      <operator activated="true" class="multiply" compatibility="6.0.009" expanded="true" height="94" name="Multiply" width="90" x="179" y="75"/>
      <operator activated="true" class="k_nn" compatibility="6.0.009" expanded="true" height="76" name="k-NN" width="90" x="312" y="30"/>
      <operator activated="true" class="decision_tree" compatibility="6.0.009" expanded="true" height="76" name="Decision Tree" width="90" x="312" y="120"/>
      <operator activated="true" class="collect" compatibility="6.0.009" expanded="true" height="94" name="Collect" width="90" x="447" y="75"/>
      <operator activated="true" class="retrieve" compatibility="6.0.009" expanded="true" height="60" name="Retrieve Golf-Testset" width="90" x="45" y="210">
        <parameter key="repository_entry" value="//Samples/data/Golf-Testset"/>
      </operator>
      <operator activated="true" class="multiply" compatibility="6.0.009" expanded="true" height="94" name="Multiply (2)" width="90" x="581" y="75"/>
      <operator activated="true" class="select" compatibility="6.0.009" expanded="true" height="60" name="Select (2)" width="90" x="714" y="120">
        <parameter key="index" value="2"/>
      </operator>
      <operator activated="true" class="select" compatibility="6.0.009" expanded="true" height="60" name="Select" width="90" x="714" y="30"/>
      <operator activated="true" class="multiply" compatibility="6.0.009" expanded="true" height="94" name="Multiply (3)" width="90" x="179" y="209"/>
      <operator activated="true" class="apply_model" compatibility="6.0.009" expanded="true" height="76" name="Apply Model (2)" width="90" x="849" y="165">
        <list key="application_parameters"/>
      </operator>
      <operator activated="true" class="apply_model" compatibility="6.0.009" expanded="true" height="76" name="Apply Model" width="90" x="849" y="75">
        <list key="application_parameters"/>
      </operator>
      <connect from_op="Retrieve Golf" from_port="output" to_op="Multiply" to_port="input"/>
      <connect from_op="Multiply" from_port="output 1" to_op="k-NN" to_port="training set"/>
      <connect from_op="Multiply" from_port="output 2" to_op="Decision Tree" to_port="training set"/>
      <connect from_op="k-NN" from_port="model" to_op="Collect" to_port="input 1"/>
      <connect from_op="Decision Tree" from_port="model" to_op="Collect" to_port="input 2"/>
      <connect from_op="Collect" from_port="collection" to_op="Multiply (2)" to_port="input"/>
      <connect from_op="Retrieve Golf-Testset" from_port="output" to_op="Multiply (3)" to_port="input"/>
      <connect from_op="Multiply (2)" from_port="output 1" to_op="Select" to_port="collection"/>
      <connect from_op="Multiply (2)" from_port="output 2" to_op="Select (2)" to_port="collection"/>
      <connect from_op="Select (2)" from_port="selected" to_op="Apply Model (2)" to_port="model"/>
      <connect from_op="Select" from_port="selected" to_op="Apply Model" to_port="model"/>
      <connect from_op="Multiply (3)" from_port="output 1" to_op="Apply Model" to_port="unlabelled data"/>
      <connect from_op="Multiply (3)" from_port="output 2" to_op="Apply Model (2)" to_port="unlabelled data"/>
      <connect from_op="Apply Model (2)" from_port="labelled data" to_port="result 2"/>
      <connect from_op="Apply Model" from_port="labelled data" to_port="result 1"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
      <portSpacing port="sink_result 3" spacing="0"/>
    </process>
  </operator>
</process>

Regards,
Marco

 3 
 on: Today at 02:42:34 PM 
Started by veve - Last post by veve


I used the select operator, but he still said that he is was expecting a model but he reveived an ioobject ...

 4 
 on: Today at 02:31:49 PM 
Started by lukki - Last post by lukki
(I use Rapidminer 5.3.015)

Hi all,

here my situation: I build a process with different models (e.g.: LinearRegression, LinearRegression with ForwardSelection, LinearRegression with OptimizeParameterEvolutionary, M5P, M5P with ForwardSelection, M5P with OptimizeParameterEvolutionary, etc.) and than use the t-Test to compare the models to find the best one.

Is there a possibility to find the best-fitting model in rapidminer and get onle the best-fitting model in the results?

Greetings,
Sebastian

 5 
 on: Today at 12:16:58 PM 
Started by fmon - Last post by Marius
You probably used a X-Validation to estimate the AUC. As you know, the X-Validation does 10 iterations, calculates the AUC for each, and delivers the average. The +-0.04 is the standard deviation of the AUC over the 10 iterations.

Regarding the ROC plot, did you see these articles?
- http://rapid-i.com/rapidforum/index.php/topic,5698.msg20162.html#msg20162
- http://rapid-i.com/rapidforum/index.php/topic,4713.0.html

Best regards,
Marius

 6 
 on: Today at 12:15:10 PM 
Started by Marius - Last post by Marius
This topic has been moved to Development.

http://rapid-i.com/rapidforum/index.php?topic=8097.0

 7 
 on: Today at 12:08:57 PM 
Started by dhancock - Last post by Marius
You can also convert the Centroid Cluster Model to an example set via "Extract Cluster Prototypes". This will output the center of each cluster in the model.

Best regards,
Marius

 8 
 on: Today at 12:06:43 PM 
Started by monamahfouz - Last post by Marius
Hi Mona,

you don't need any Text Processing operators (in the RapidMiner sense) at all. First let's ignore the multi-tag rows:
Load your data, and add a Filter Examples operator with the attribute_value_filter "Hashtag != .* .*" (without the quotes).
Then add an Aggregate operator. Group by Hashtag and add the aggregation function count for Hashtag. That's it Smiley

Best regards,
Marius

 9 
 on: Today at 07:35:18 AM 
Started by hagen85 - Last post by Marco Boeck
Hi,

does the problem still exist with Studio 6.0.008?
If so, what exactly does not work? Can you access Statistics/Data for the result, but not Charts? Can you describe the data that still blocks the Charts, i.e. number of rows/attributes and the statistics for your attributes (right-click on the background of the Statistics view and select "Copy statistics to clipboard" to be able to paste them somewhere).

Regards,
Marco

 10 
 on: Today at 07:25:55 AM 
Started by bugrasitemkar - Last post by Marco Boeck
Hi,

I have merged both topis. The documentation could indeed be improved here. It's on our internal issue list Smiley

Regards,
Marco

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