"Using Weka models with Model Management extension"

sgenzer

Hi...anyone having trouble using the Weka models (e.g. W-J48) with the Model Management extension?  I tried to use two models to compare (Decision Tree and W-J48) and it did NOT like it.

Scott

Thomas_Ott

I haven't tried it but maybe ping @bhupendra_patil? I think he was a key author for this extension. 

MartinLiebig

Scott,

 

i've tried to reproduce it. I can add a J48 into the collection. There is some issue with the meta data, but it runs smoothly. Can you explain a bit more what your issue is?

 

Best,

Martin

 

<?xml version="1.0" encoding="UTF-8"?><process version="7.5.001">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="7.5.001" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="retrieve" compatibility="7.5.001" expanded="true" height="68" name="Retrieve Golf" width="90" x="45" y="85">
        <parameter key="repository_entry" value="//Samples/data/Golf"/>
      </operator>
      <operator activated="true" class="multiply" compatibility="7.5.001" expanded="true" height="124" name="Multiply" width="90" x="179" y="85"/>
      <operator activated="true" class="weka:W-J48" compatibility="7.3.001-SNAPSHOT" expanded="true" height="82" name="W-J48" width="90" x="380" y="34"/>
      <operator activated="true" class="concurrency:parallel_decision_tree" compatibility="7.5.001" expanded="true" height="82" name="Decision Tree" width="90" x="380" y="238"/>
      <operator activated="true" class="h2o:deep_learning" compatibility="7.2.000" expanded="true" height="82" name="Deep Learning" width="90" x="380" y="136">
        <enumeration key="hidden_layer_sizes">
          <parameter key="hidden_layer_sizes" value="50"/>
          <parameter key="hidden_layer_sizes" value="50"/>
        </enumeration>
        <enumeration key="hidden_dropout_ratios"/>
        <list key="expert_parameters"/>
        <list key="expert_parameters_"/>
      </operator>
      <operator activated="false" class="k_nn" compatibility="7.5.001" expanded="true" height="82" name="k-NN" width="90" x="112" y="340"/>
      <operator activated="true" class="retrieve" compatibility="7.5.001" expanded="true" height="68" name="Retrieve Golf-Testset (2)" width="90" x="648" y="493">
        <parameter key="repository_entry" value="//Samples/data/Golf-Testset"/>
        <description align="center" color="transparent" colored="false" width="126">This is our test dataset to compare models</description>
      </operator>
      <operator activated="true" class="collect" compatibility="7.5.001" expanded="true" height="124" name="Collect" width="90" x="648" y="34">
        <description align="center" color="transparent" colored="false" width="126">We will create a collection of models to test</description>
      </operator>
      <operator activated="true" class="model_management:model_management_key" compatibility="7.3.000" expanded="true" height="103" name="Compare Models" width="90" x="849" y="136">
        <parameter key="folder" value="//Local Repository/Model Management/Project 1"/>
        <parameter key="date_format" value="yyyy_MM_dd_HH_mm"/>
        <process expanded="true">
          <operator activated="true" class="apply_model" compatibility="7.5.001" expanded="true" height="82" name="Apply Model (2)" width="90" x="447" y="136">
            <list key="application_parameters"/>
          </operator>
          <operator activated="true" class="performance" compatibility="7.5.001" expanded="true" height="82" name="Performance (2)" width="90" x="715" y="34"/>
          <connect from_port="model" to_op="Apply Model (2)" to_port="model"/>
          <connect from_port="test data" 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="Apply Model (2)" from_port="model" to_port="model"/>
          <connect from_op="Performance (2)" from_port="performance" to_port="performance"/>
          <portSpacing port="source_model" spacing="0"/>
          <portSpacing port="source_test data" spacing="0"/>
          <portSpacing port="source_in 1" spacing="0"/>
          <portSpacing port="sink_performance" spacing="0"/>
          <portSpacing port="sink_model" spacing="0"/>
          <portSpacing port="sink_out 1" spacing="0"/>
        </process>
      </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="W-J48" to_port="training set"/>
      <connect from_op="Multiply" from_port="output 2" to_op="Deep Learning" to_port="training set"/>
      <connect from_op="Multiply" from_port="output 3" to_op="Decision Tree" to_port="training set"/>
      <connect from_op="W-J48" from_port="model" to_op="Collect" to_port="input 1"/>
      <connect from_op="Decision Tree" from_port="model" to_op="Collect" to_port="input 3"/>
      <connect from_op="Deep Learning" from_port="model" to_op="Collect" to_port="input 2"/>
      <connect from_op="Retrieve Golf-Testset (2)" from_port="output" to_op="Compare Models" to_port="test data"/>
      <connect from_op="Collect" from_port="collection" to_op="Compare Models" to_port="model collection"/>
      <connect from_op="Compare Models" from_port="performance" to_port="result 1"/>
      <connect from_op="Compare Models" from_port="model" to_port="result 2"/>
      <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"/>
      <description align="center" color="yellow" colored="false" height="138" resized="false" width="180" x="335" y="336">We are going to build three different models here.&lt;br/&gt;&lt;br/&gt;You can also attach models from Repository if you wish to compare them against the three models built here</description>
    </process>
  </operator>
</process>

sgenzer

Hi Martin -

It did not like mixing the weka model with the RM decision tree model. Interesting that you got it to work. I've had problems in the past with this...can you see if you can save a Weka J48 model to your repository and then use it in another new process with Apply Model? I've never been able to get this to work either. Yes maybe a meta data issue...don't really know.

Thanks.
Scott