NaN Values on Logistic Regression Output

B00100719

Why would this be happening?
All numeric input - missing values are being replaced with averages before going into the LG operator

5 of my 25 inputs are returning NULL outputs?  
I need the p-values

It's driving me nuts!

B00100719

PROCESS.......

<?xml version="1.0" encoding="UTF-8"?><process version="9.3.001">

  <context>

    <input/>

    <output/>

    <macros/>

  </context>

  <operator activated="true" class="process" compatibility="9.3.001" expanded="true" name="Process">

    <parameter key="logverbosity" value="init"/>

    <parameter key="random_seed" value="2001"/>

    <parameter key="send_mail" value="never"/>

    <parameter key="notification_email" value=""/>

    <parameter key="process_duration_for_mail" value="30"/>

    <parameter key="encoding" value="SYSTEM"/>

    <process expanded="true">

      <operator activated="true" class="retrieve" compatibility="9.3.001" expanded="true" height="68" name="Retrieve ALL_KD_THESIS_WITH_WEIGHTED_CHR_35_MEASURES (2)" width="90" x="313" y="34">

        <parameter key="repository_entry" value="../../data/ALL_KD_THESIS_WITH_WEIGHTED_CHR_35_MEASURES"/>

      </operator>

      <operator activated="true" class="replace_missing_values" compatibility="9.3.001" expanded="true" height="103" name="Replace Missing Values" width="90" x="514" y="34">

        <parameter key="return_preprocessing_model" value="false"/>

        <parameter key="create_view" value="false"/>

        <parameter key="attribute_filter_type" value="all"/>

        <parameter key="attribute" value=""/>

        <parameter key="attributes" value=""/>

        <parameter key="use_except_expression" value="false"/>

        <parameter key="value_type" value="attribute_value"/>

        <parameter key="use_value_type_exception" value="false"/>

        <parameter key="except_value_type" value="time"/>

        <parameter key="block_type" value="attribute_block"/>

        <parameter key="use_block_type_exception" value="false"/>

        <parameter key="except_block_type" value="value_matrix_row_start"/>

        <parameter key="invert_selection" value="false"/>

        <parameter key="include_special_attributes" value="false"/>

        <parameter key="default" value="average"/>

        <list key="columns"/>

        <parameter key="replenishment_value" value="52"/>

      </operator>

      <operator activated="true" class="numerical_to_binominal" compatibility="9.3.001" expanded="true" height="82" name="Numerical to Binominal" width="90" x="648" y="34">

        <parameter key="attribute_filter_type" value="single"/>

        <parameter key="attribute" value="actual_ss_ct"/>

        <parameter key="attributes" value=""/>

        <parameter key="use_except_expression" value="false"/>

        <parameter key="value_type" value="numeric"/>

        <parameter key="use_value_type_exception" value="false"/>

        <parameter key="except_value_type" value="real"/>

        <parameter key="block_type" value="value_series"/>

        <parameter key="use_block_type_exception" value="false"/>

        <parameter key="except_block_type" value="value_series_end"/>

        <parameter key="invert_selection" value="false"/>

        <parameter key="include_special_attributes" value="true"/>

        <parameter key="min" value="0.0"/>

        <parameter key="max" value="0.0"/>

      </operator>

      <operator activated="true" class="set_role" compatibility="9.3.001" expanded="true" height="82" name="Set Role" width="90" x="782" y="34">

        <parameter key="attribute_name" value="actual_ss_ct"/>

        <parameter key="target_role" value="label"/>

        <list key="set_additional_roles">

          <parameter key="I_CLM" value="id"/>

          <parameter key="actual_ss_ct" value="label"/>

        </list>

      </operator>

      <operator activated="true" class="normalize" compatibility="9.3.001" expanded="true" height="103" name="Normalize" width="90" x="983" y="34">

        <parameter key="return_preprocessing_model" value="false"/>

        <parameter key="create_view" value="false"/>

        <parameter key="attribute_filter_type" value="all"/>

        <parameter key="attribute" value=""/>

        <parameter key="attributes" value=""/>

        <parameter key="use_except_expression" value="false"/>

        <parameter key="value_type" value="numeric"/>

        <parameter key="use_value_type_exception" value="false"/>

        <parameter key="except_value_type" value="real"/>

        <parameter key="block_type" value="value_series"/>

        <parameter key="use_block_type_exception" value="false"/>

        <parameter key="except_block_type" value="value_series_end"/>

        <parameter key="invert_selection" value="false"/>

        <parameter key="include_special_attributes" value="false"/>

        <parameter key="method" value="Z-transformation"/>

        <parameter key="min" value="0.0"/>

        <parameter key="max" value="1.0"/>

        <parameter key="allow_negative_values" value="false"/>

      </operator>

      <operator activated="true" class="h2o:logistic_regression" compatibility="9.3.001" expanded="true" height="124" name="Logistic Regression (2)" width="90" x="1117" y="34">

        <parameter key="solver" value="AUTO"/>

        <parameter key="reproducible" value="false"/>

        <parameter key="maximum_number_of_threads" value="4"/>

        <parameter key="use_regularization" value="false"/>

        <parameter key="lambda_search" value="false"/>

        <parameter key="number_of_lambdas" value="0"/>

        <parameter key="lambda_min_ratio" value="0.0"/>

        <parameter key="early_stopping" value="true"/>

        <parameter key="stopping_rounds" value="3"/>

        <parameter key="stopping_tolerance" value="0.001"/>

        <parameter key="standardize" value="true"/>

        <parameter key="non-negative_coefficients" value="false"/>

        <parameter key="add_intercept" value="true"/>

        <parameter key="compute_p-values" value="true"/>

        <parameter key="remove_collinear_columns" value="true"/>

        <parameter key="missing_values_handling" value="MeanImputation"/>

        <parameter key="max_iterations" value="1"/>

        <parameter key="max_runtime_seconds" value="20"/>

      </operator>

      <connect from_op="Retrieve ALL_KD_THESIS_WITH_WEIGHTED_CHR_35_MEASURES (2)" 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="Numerical to Binominal" to_port="example set input"/>

      <connect from_op="Numerical to Binominal" 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="Normalize" to_port="example set input"/>

      <connect from_op="Normalize" from_port="example set output" to_op="Logistic Regression (2)" to_port="training set"/>

      <connect from_op="Logistic Regression (2)" 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>