Problem with feature evaluation using YAGGA2

andyknownasabu

Dear all,

I've managed to set up the first working RM chain for feature evaluation -
At least I think so, because I see the following error message on the console:

G Feb 4, 2009 9:15:11 AM: [Warning] Cannot generate test attribute: No such attribute: corr. We just keep both attributes fo
r sure...
Last message repeated 2 times.

The chain looks as follows:

<?xml version="1.0" encoding="US-ASCII"?>
<process version="4.3">

  <operator name="Root" class="Process" expanded="yes">
      <operator name="Data Source" class="ArffExampleSource">
          <parameter key="data_file"    value="all_subjects.arff"/>
          <parameter key="id_attribute" value="id"/>
          <parameter key="label_attribute"      value="label"/>
      </operator>
      <operator name="YAGGA2" class="YAGGA2" expanded="yes">
          <parameter key="use_diff"     value="true"/>
          <parameter key="use_max"      value="true"/>
          <parameter key="use_min"      value="true"/>
          <parameter key="use_sin"      value="false"/>
          <parameter key="use_square_roots"     value="true"/>
          <operator name="SimpleValidation" class="SimpleValidation" expanded="yes">
              <parameter key="create_complete_model"    value="true"/>
              <operator name="DecisionTree" class="DecisionTree">
                  <parameter key="criterion"    value="gini_index"/>
                  <parameter key="maximal_depth"        value="5"/>
              </operator>
              <operator name="Applier Chain" class="OperatorChain" expanded="yes">
                  <operator name="Test" class="ModelApplier">
                      <list key="application_parameters">
                      </list>
                      <parameter key="keep_model"       value="true"/>
                  </operator>
                  <operator name="ClassificationPerformance" class="ClassificationPerformance">
                      <parameter key="keep_example_set" value="true"/>
                      <parameter key="root_mean_squared_error"  value="true"/>
                      <parameter key="root_relative_squared_error"      value="true"/>
                      <parameter key="weighted_mean_precision"  value="true"/>
                      <parameter key="weighted_mean_recall"     value="true"/>
                  </operator>
              </operator>
          </operator>
          <operator name="ProcessLog" class="ProcessLog">
              <parameter key="filename" value="process_log.txt"/>
              <list key="log">
                <parameter key="Generation"     value="operator.YAGGA2.value.generation"/>
                <parameter key="Recall" value="operator.ClassificationPerformance.value.weighted_mean_recall"/>
                <parameter key="Precision"      value="operator.ClassificationPerformance.value.weighted_mean_precision"/>
              </list>
          </operator>
      </operator>
      <operator name="AttributeWeightsWriter" class="AttributeWeightsWriter">
          <parameter key="attribute_weights_file"       value="attribute.wgt"/>
      </operator>
      <operator name="PerformanceWriter" class="PerformanceWriter">
          <parameter key="performance_file"     value="performance.per"/>
      </operator>
      <operator name="AttributeConstructionsWriter" class="AttributeConstructionsWriter">
          <parameter key="attribute_constructions_file" value="attribute.cst"/>
      </operator>
  </operator>

</process>

Can anybody explain to me why this error occurs, what it means, how to fix it (if possible) and in general if the above
scheme makes sense at all? I'd highly appreciate to hear from your experience and concerning how to improve the above process.

Thank you very much and best regards!

BAMBAMBAM

I am having the same problem with YAGGA2 (but not with YAGGA).  I get these errors 1000's of times:

G Aug 17, 2009 9:00:00 PM: [Warning] exp: Infinite value generated, replaced by NaN.
G Aug 17, 2009 9:00:00 PM: [Warning] exp: NaN generated.
G Aug 17, 2009 9:00:00 PM: [Warning] 1/: NaN generated.
Last message repeated 5 times.
G Aug 17, 2009 9:00:00 PM: [Warning] /: Infinite value generated.
Last message repeated 105 times.
....
G Aug 17, 2009 9:02:13 PM: [Warning] Cannot generate test attribute: No such attribute: BB202CBas / LRAll1CUpr2. We just keep both attributes for sure...
Last message repeated 20880 times.

I think it is a bug with YAGGA2 since I don't have the problem when I replace YAGGA2 with YAGGA.  It seems that, when there is a problem with a generated attribute (NaN or infinity error) then the code doesn't deal with the situation gracefully.


This is my XML:
<operator name="Root" class="Process" expanded="yes">
    <operator name="CSVExampleSource" class="CSVExampleSource">
        <parameter key="filename" value="Minutes.csv"/>
        <parameter key="label_name" value="RRRatio"/>
        <parameter key="id_name" value="id"/>
        <parameter key="sample_ratio" value="0.05"/>
    </operator>
    <operator name="AttributeFilter" class="AttributeFilter">
        <parameter key="condition_class" value="attribute_name_filter"/>
        <parameter key="parameter_string" value="Symbol|Bar|BarDate|BarTime|HighestHighAfter|HighestLowAfter|LowestHighAfter|LowestLowAfter|VWAvgHighAfter|VWAvgLowAfter|MaxLongLoss|MaxShortLoss|LongAvgProfit|ShortAvgProfit"/>
        <parameter key="invert_filter" value="true"/>
    </operator>
    <operator name="YAGGA2" class="YAGGA2" expanded="yes">
        <parameter key="population_size" value="100"/>
        <parameter key="maximum_number_of_generations" value="1000"/>
        <parameter key="generations_without_improval" value="10"/>
        <parameter key="p_initialize" value="0.1"/>
        <parameter key="use_plus" value="false"/>
        <parameter key="use_diff" value="true"/>
        <parameter key="use_div" value="true"/>
        <parameter key="use_square_roots" value="true"/>
        <parameter key="use_sin" value="false"/>
        <parameter key="use_log" value="true"/>
        <parameter key="use_absolute_values" value="false"/>
        <parameter key="constant_generation_prob" value="0.0"/>
        <operator name="SimpleValidation" class="SimpleValidation" expanded="yes">
            <parameter key="local_random_seed" value="10"/>
            <operator name="W-REPTree" class="W-REPTree">
                <parameter key="M" value="1000.0"/>
            </operator>
            <operator name="ApplierChain" class="OperatorChain" expanded="yes">
                <operator name="Applier" class="ModelApplier">
                    <list key="application_parameters">
                    </list>
                </operator>
                <operator name="RegressionPerformance" class="RegressionPerformance">
                    <parameter key="keep_example_set" value="true"/>
                    <parameter key="spearman_rho" value="true"/>
                    <parameter key="use_example_weights" value="false"/>
                </operator>
            </operator>
        </operator>
        <operator name="ProcessLog" class="ProcessLog">
            <list key="log">
              <parameter key="generation" value="operator.YAGGA2.value.generation"/>
              <parameter key="performance" value="operator.YAGGA2.value.performance"/>
              <parameter key="best" value="operator.YAGGA2.value.best"/>
            </list>
        </operator>
    </operator>
    <operator name="AttributeConstructionsWriter" class="AttributeConstructionsWriter" breakpoints="after">
        <parameter key="attribute_constructions_file" value="MinuteYagga100.att"/>
    </operator>
    <operator name="AttributeWeightsWriter" class="AttributeWeightsWriter" breakpoints="after">
        <parameter key="attribute_weights_file" value="MinuteYagga100.wgt"/>
    </operator>
</operator>