"Error:Beginner"

catchyoulater

Hi,
    I'm a beginner of Rapidminer.An error came out, when I used it.The text of Error is:Input example set must have special attribute label. It made me confused because  I had  selected  an attribute when I read the data table from Database. The detail of the XML is:
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.0">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" expanded="true" name="Process">
    <parameter key="logfile" value="E:\test\samples\processes\test\first1.log"/>
    <parameter key="resultfile" value="E:\test\samples\data\first1.res"/>
    <process expanded="true" height="419" width="570">
      <operator activated="true" class="read_database" expanded="true" height="60" name="Read Database" width="90" x="45" y="30">
        <parameter key="database_system" value="Microsoft SQL Server (JTDS)"/>
        <parameter key="database_url" value="jdbc:jtds:sqlserver://127.0.0.1:1433/kdd"/>
        <parameter key="username" value="ling"/>
        <parameter key="password" value="IBgRiRv1A6A="/>
        <parameter key="query" value="SELECT [Var5], [Var6], [Var165], [Var166], [Var167], [Var168], [appetency], [id] FROM [orange_small_train]"/>
        <parameter key="table_name" value="orange_small_train"/>
        <parameter key="label_attribute" value="appetency"/>
        <parameter key="id_attribute" value="id"/>
      </operator>
      <operator activated="true" class="replace_missing_values" expanded="true" height="94" name="Replace Missing Values" width="90" x="179" y="30">
        <parameter key="default" value="none"/>
        <list key="columns"/>
      </operator>
      <operator activated="true" class="decision_tree" expanded="true" height="76" name="Decision Tree" width="90" x="315" y="30"/>
      <connect from_op="Read Database" from_port="output" to_op="Replace Missing Values" to_port="example set input"/>
      <connect from_op="Replace Missing Values" from_port="example set output" to_op="Decision Tree" to_port="training set"/>
      <connect from_op="Decision Tree" from_port="model" 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"/>
    </process>
  </operator>
</process>

    Looking forward to you reply.

TobiasMalbrecht

Hi,

you may verify if your data contains a label if you place a breakpoint at the [tt]Read Database[/tt] operator and inspect the resulting data set. It might be that the functionality concerning setting a label in the database reader is broken since we did some refactoring in the input operators. This will of course be fixed in the final version of RM 5 at the latest. As a workaround, you can use the operator [tt]Set Role[/tt] after loading the data to mark an attribute as label.

Kind regards,
Tobias

catchyoulater

Hi,Tobias
    thanks for your reply. I tried to follow what you said in the  reply by insetting the operator, Role set, behind the operator of Read Database and entering the name of the target attribute which I want to set it as label.  But then a confusing error appeared: The attribute appetency is missing in the input example set. (note: ‘appetency’ is the name of the target attribute). I ignored the error, run the process. To my surprise, the result was right. (There is a information copied from the results workspace: label: appetency (nominal in {-1, 1 }; no missing values) ).Then I used the result data for the process of Decision Tree, but the same error appeared: Input example set must have special attribute label. What’s the matter on earth?
    Looking forward to your reply.