Write Model

Hi,

I have a problem by saving a Neural Net Model using the "Write Model" operator.

Rapid Miner stops with a severe error but there is no further information about the problem. I tried it with all file formats.

Process:

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.3.015">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="5.3.015" expanded="true" name="Process">
    <process expanded="true">
      <operator activated="true" class="open_file" compatibility="5.3.015" expanded="true" height="60" name="Open File (2)" width="90" x="45" y="255">
        <parameter key="filename" value="/home/ubuntu/test.csv"/>
      </operator>
      <operator activated="true" class="read_csv" compatibility="5.3.015" expanded="true" height="60" name="Read CSV (2)" width="90" x="45" y="165">
        <parameter key="csv_file" value="/home/ubuntu/test.csv"/>
        <parameter key="trim_lines" value="true"/>
        <parameter key="first_row_as_names" value="false"/>
        <list key="annotations">
          <parameter key="0" value="Name"/>
        </list>
        <parameter key="encoding" value="UTF-8"/>
        <list key="data_set_meta_data_information"/>
      </operator>
      <operator activated="true" class="remove_useless_attributes" compatibility="5.3.015" expanded="true" height="76" name="Remove Useless Attributes" width="90" x="45" y="30"/>
      <operator activated="true" class="remove_correlated_attributes" compatibility="5.3.015" expanded="true" height="76" name="Remove Correlated Attributes" width="90" x="179" y="30"/>
      <operator activated="true" class="filter_examples" compatibility="5.3.015" expanded="true" height="76" name="Filter Examples" width="90" x="246" y="210">
        <parameter key="condition_class" value="missing_attributes"/>
      </operator>
      <operator activated="true" class="set_role" compatibility="5.3.015" expanded="true" height="76" name="Set Role (2)" width="90" x="447" y="255">
        <parameter key="attribute_name" value="label"/>
        <parameter key="target_role" value="label"/>
        <list key="set_additional_roles"/>
      </operator>
      <operator activated="true" class="filter_examples" compatibility="5.3.015" expanded="true" height="76" name="Filter Examples (2)" width="90" x="380" y="120">
        <parameter key="condition_class" value="no_missing_attributes"/>
      </operator>
      <operator activated="true" class="set_role" compatibility="5.3.015" expanded="true" height="76" name="Set Role" width="90" x="447" y="30">
        <parameter key="attribute_name" value="label"/>
        <parameter key="target_role" value="label"/>
        <list key="set_additional_roles"/>
      </operator>
      <operator activated="true" class="neural_net" compatibility="5.3.015" expanded="true" height="76" name="Neural Net" width="90" x="581" y="75">
        <list key="hidden_layers"/>
      </operator>
      <operator activated="true" class="apply_model" compatibility="5.3.015" expanded="true" height="76" name="Apply Model" width="90" x="715" y="120">
        <list key="application_parameters"/>
      </operator>
      <operator activated="true" class="write_model" compatibility="5.3.015" expanded="true" height="60" name="Write Model" width="90" x="782" y="255">
        <parameter key="model_file" value="/home/ubuntu/models/model.xml"/>
        <parameter key="output_type" value="XML"/>
      </operator>
      <operator activated="false" class="weka:W-SMO" compatibility="5.3.001" expanded="true" height="76" name="W-SMO" width="90" x="179" y="390"/>
      <connect from_op="Open File (2)" from_port="file" to_op="Read CSV (2)" to_port="file"/>
      <connect from_op="Read CSV (2)" from_port="output" to_op="Remove Useless Attributes" to_port="example set input"/>
      <connect from_op="Remove Useless Attributes" from_port="example set output" to_op="Remove Correlated Attributes" to_port="example set input"/>
      <connect from_op="Remove Correlated Attributes" from_port="example set output" to_op="Filter Examples" to_port="example set input"/>
      <connect from_op="Filter Examples" from_port="example set output" to_op="Set Role (2)" to_port="example set input"/>
      <connect from_op="Filter Examples" from_port="original" to_op="Filter Examples (2)" to_port="example set input"/>
      <connect from_op="Set Role (2)" from_port="example set output" to_op="Apply Model" to_port="unlabelled data"/>
      <connect from_op="Filter Examples (2)" from_port="example set output" to_op="Set Role" to_port="example set input"/>
      <connect from_op="Set Role" from_port="example set output" to_op="Neural Net" to_port="training set"/>
      <connect from_op="Neural Net" from_port="model" to_op="Apply Model" to_port="model"/>
      <connect from_op="Apply Model" from_port="labelled data" to_port="result 1"/>
      <connect from_op="Apply Model" from_port="model" to_op="Write Model" to_port="input"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
    </process>
  </operator>
</process>