[SOLVED] Error:Deviaion of performance was NAN

Hi

I used evolutionary optimization operator to optimize select by weights operator and nu-SVR at the same time. but in the log wiev, i encountered the error "PM WARNING: SimpleCriterion: Deviation of Performance was NaN!". How can i fix the problem? Please i am waiting for your help

My model xml are:

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.2.008">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="5.2.008" expanded="true" name="Process">
    <parameter key="parallelize_main_process" value="true"/>
    <process expanded="true" height="400" width="480">
      <operator activated="true" class="retrieve" compatibility="5.2.008" expanded="true" height="60" name="Retrieve" width="90" x="45" y="30">
        <parameter key="repository_entry" value="//kenan/Tarih/20.11.2012/Clus3/ClusByKMeans(Fast)Euclidian"/>
      </operator>
      <operator activated="true" class="weight_by_relief" compatibility="5.2.008" expanded="true" height="76" name="Weight by Relief" width="90" x="180" y="30"/>
      <operator activated="true" class="parallel:optimize_parameters_evolutionary_parallel" compatibility="5.1.000" expanded="true" height="148" name="Optimize Parameters (Evolutionary)" width="90" x="313" y="210">
        <list key="parameters">
          <parameter key="Select by Weights (2).k" value="[15;35]"/>
          <parameter key="SVM (2).gamma" value="[0.0;0.01]"/>
          <parameter key="SVM (2).nu" value="[0.0;0.5]"/>
          <parameter key="SVM (2).C" value="[0.0;0.01]"/>
          <parameter key="SVM (2).epsilon" value="[0.0;0.01]"/>
        </list>
        <parameter key="max_generations" value="90"/>
        <parameter key="population_size" value="6"/>
        <parameter key="crossover_prob" value="0.8"/>
        <parameter key="number_of_threads" value="8"/>
        <parameter key="parallelize_optimization_process" value="true"/>
        <process expanded="true" height="400" width="632">
          <operator activated="true" class="select_by_weights" compatibility="5.2.008" expanded="true" height="94" name="Select by Weights (2)" width="90" x="45" y="30">
            <parameter key="weight_relation" value="top k"/>
            <parameter key="k" value="16"/>
          </operator>
          <operator activated="true" class="split_validation" compatibility="5.1.002" expanded="true" height="112" name="Validation (2)" width="90" x="380" y="30">
            <parameter key="split_ratio" value="0.9"/>
            <parameter key="sampling_type" value="linear sampling"/>
            <parameter key="parallelize_training" value="true"/>
            <parameter key="parallelize_testing" value="true"/>
            <process expanded="true" height="400" width="165">
              <operator activated="true" class="support_vector_machine_libsvm" compatibility="5.2.008" expanded="true" height="76" name="SVM (2)" width="90" x="45" y="30">
                <parameter key="svm_type" value="nu-SVR"/>
                <parameter key="gamma" value="0.0018245416895055634"/>
                <parameter key="C" value="0.00562070136566738"/>
                <parameter key="nu" value="0.48424641085734477"/>
                <parameter key="epsilon" value="0.009366372796859642"/>
                <list key="class_weights"/>
              </operator>
              <connect from_port="training" to_op="SVM (2)" to_port="training set"/>
              <connect from_op="SVM (2)" from_port="model" to_port="model"/>
              <portSpacing port="source_training" spacing="0"/>
              <portSpacing port="sink_model" spacing="0"/>
              <portSpacing port="sink_through 1" spacing="0"/>
            </process>
            <process expanded="true" height="400" width="300">
              <operator activated="true" class="apply_model" compatibility="5.2.008" expanded="true" height="76" name="Apply Model (2)" width="90" x="45" y="30">
                <list key="application_parameters"/>
              </operator>
              <operator activated="true" class="performance_regression" compatibility="5.2.008" expanded="true" height="76" name="Performance (2)" width="90" x="180" y="30">
                <parameter key="main_criterion" value="root_mean_squared_error"/>
                <parameter key="absolute_error" value="true"/>
                <parameter key="relative_error" value="true"/>
                <parameter key="root_relative_squared_error" value="true"/>
                <parameter key="squared_error" value="true"/>
                <parameter key="squared_correlation" value="true"/>
                <parameter key="spearman_rho" value="true"/>
                <parameter key="kendall_tau" value="true"/>
              </operator>
              <connect from_port="model" to_op="Apply Model (2)" to_port="model"/>
              <connect from_port="test set" to_op="Apply Model (2)" to_port="unlabelled data"/>
              <connect from_op="Apply Model (2)" from_port="labelled data" to_op="Performance (2)" to_port="labelled data"/>
              <connect from_op="Performance (2)" from_port="performance" to_port="averagable 1"/>
              <portSpacing port="source_model" spacing="0"/>
              <portSpacing port="source_test set" spacing="0"/>
              <portSpacing port="source_through 1" spacing="0"/>
              <portSpacing port="sink_averagable 1" spacing="0"/>
              <portSpacing port="sink_averagable 2" spacing="0"/>
            </process>
          </operator>
          <connect from_port="input 1" to_op="Select by Weights (2)" to_port="weights"/>
          <connect from_port="input 2" to_op="Select by Weights (2)" to_port="example set input"/>
          <connect from_op="Select by Weights (2)" from_port="example set output" to_op="Validation (2)" to_port="training"/>
          <connect from_op="Select by Weights (2)" from_port="weights" to_port="result 3"/>
          <connect from_op="Validation (2)" from_port="model" to_port="result 1"/>
          <connect from_op="Validation (2)" from_port="training" to_port="result 2"/>
          <connect from_op="Validation (2)" from_port="averagable 1" to_port="performance"/>
          <portSpacing port="source_input 1" spacing="0"/>
          <portSpacing port="source_input 2" spacing="0"/>
          <portSpacing port="source_input 3" spacing="0"/>
          <portSpacing port="sink_performance" spacing="0"/>
          <portSpacing port="sink_result 1" spacing="0"/>
          <portSpacing port="sink_result 2" spacing="0"/>
          <portSpacing port="sink_result 3" spacing="0"/>
          <portSpacing port="sink_result 4" spacing="0"/>
        </process>
      </operator>
      <operator activated="true" class="log" compatibility="5.2.008" expanded="true" height="76" name="Log" width="90" x="380" y="30">
        <parameter key="filename" value="C:\Users\KenanB\Desktop\RapidminerLog\ParameterLog.txt"/>
        <list key="log">
          <parameter key="ApplyCount" value="operator.Optimize Parameters (Evolutionary).value.applycount"/>
          <parameter key="RMSE" value="operator.Performance (2).value.root_mean_squared_error"/>
          <parameter key="K" value="operator.Select by Weights (2).parameter.k"/>
          <parameter key="C" value="operator.SVM (2).parameter.C"/>
          <parameter key="NU" value="operator.SVM (2).parameter.nu"/>
          <parameter key="Gamma" value="operator.SVM (2).parameter.gamma"/>
          <parameter key="Epsilon" value="operator.SVM (2).parameter.epsilon"/>
        </list>
      </operator>
      <connect from_op="Retrieve" from_port="output" to_op="Weight by Relief" to_port="example set"/>
      <connect from_op="Weight by Relief" from_port="weights" to_op="Optimize Parameters (Evolutionary)" to_port="input 1"/>
      <connect from_op="Weight by Relief" from_port="example set" to_op="Optimize Parameters (Evolutionary)" to_port="input 2"/>
      <connect from_op="Optimize Parameters (Evolutionary)" from_port="performance" to_port="result 2"/>
      <connect from_op="Optimize Parameters (Evolutionary)" from_port="parameter" to_op="Log" to_port="through 1"/>
      <connect from_op="Optimize Parameters (Evolutionary)" from_port="result 1" to_port="result 3"/>
      <connect from_op="Optimize Parameters (Evolutionary)" from_port="result 2" to_port="result 4"/>
      <connect from_op="Log" from_port="through 1" 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"/>
      <portSpacing port="sink_result 4" spacing="0"/>
      <portSpacing port="sink_result 5" spacing="0"/>
    </process>
  </operator>
</process>