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"Explain Predictions" Colored Output in Results View: Exporting/Copying?

zsherwinzsherwin Member Posts: 2 Contributor I
edited November 2018 in Help

Hello,

 

The "Explain Predictions" operator color-codes the weightings of predictions in terms of their support. See the below screenshot for an example.

 

image.png

Is there a way to copy or export this data out, keeping the color coding intact? I'm aware that I can export this and also the weighting and recreate the color coding for myself, but RapidMiner has already done the work of applying the color coding to the "Explain Predictions" result set for me. I'd love to be able to get it into Excel with color coding intact. If that's not possible, it would even be sufficient to have some way of getting the data out as an image (again, with color coding intact). I've tried screenshotting software like SnagIt that can auto-scroll, but it doesn't seem to pick up RapidMiner's scrollbars.

 

I didn't see any other forum topics or KB articles on this topic.

 

Thanks!

 



<?xml version="1.0" encoding="UTF-8"?><process version="9.0.002">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="9.0.002" 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="9.0.002" expanded="true" height="68" name="Retrieve 20180521 testing" width="90" x="45" y="595">
<parameter key="repository_entry" value="../20180312 JRM/20180521 testing"/>
</operator>
<operator activated="true" class="multiply" compatibility="9.0.002" expanded="true" height="187" name="Testing" width="90" x="179" y="595"/>
<operator activated="true" class="retrieve" compatibility="9.0.002" expanded="true" height="68" name="Retrieve 20180521 training" width="90" x="45" y="136">
<parameter key="repository_entry" value="../20180312 JRM/20180521 training"/>
</operator>
<operator activated="true" class="multiply" compatibility="9.0.002" expanded="true" height="166" name="Training" width="90" x="179" y="136"/>
<operator activated="true" class="concurrency:cross_validation" compatibility="8.2.000" expanded="true" height="145" name="CV DL" width="90" x="380" y="238">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="automatic"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="h2o:deep_learning" compatibility="9.0.000" expanded="true" height="82" name="Deep Learning" width="90" x="179" y="34">
<parameter key="activation" value="Rectifier"/>
<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"/>
<parameter key="reproducible_(uses_1_thread)" value="false"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="epochs" value="10.0"/>
<parameter key="compute_variable_importances" value="false"/>
<parameter key="train_samples_per_iteration" value="-2"/>
<parameter key="adaptive_rate" value="true"/>
<parameter key="epsilon" value="1.0E-8"/>
<parameter key="rho" value="0.99"/>
<parameter key="learning_rate" value="0.005"/>
<parameter key="learning_rate_annealing" value="1.0E-6"/>
<parameter key="learning_rate_decay" value="1.0"/>
<parameter key="momentum_start" value="0.0"/>
<parameter key="momentum_ramp" value="1000000.0"/>
<parameter key="momentum_stable" value="0.0"/>
<parameter key="nesterov_accelerated_gradient" value="true"/>
<parameter key="standardize" value="true"/>
<parameter key="L1" value="1.0E-5"/>
<parameter key="L2" value="0.0"/>
<parameter key="max_w2" value="10.0"/>
<parameter key="loss_function" value="Automatic"/>
<parameter key="distribution_function" value="AUTO"/>
<parameter key="early_stopping" value="false"/>
<parameter key="stopping_rounds" value="1"/>
<parameter key="stopping_metric" value="AUTO"/>
<parameter key="stopping_tolerance" value="0.001"/>
<parameter key="missing_values_handling" value="MeanImputation"/>
<parameter key="max_runtime_seconds" value="0"/>
<list key="expert_parameters"/>
<list key="expert_parameters_"/>
</operator>
<connect from_port="training set" to_op="Deep Learning" to_port="training set"/>
<connect from_op="Deep Learning" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.0.002" expanded="true" height="82" name="Apply Model (2)" width="90" x="112" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance" compatibility="9.0.002" expanded="true" height="82" name="Performance DL" width="90" x="313" y="34">
<parameter key="use_example_weights" 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 DL" to_port="labelled data"/>
<connect from_op="Performance DL" from_port="performance" to_port="performance 1"/>
<connect from_op="Performance DL" from_port="example set" to_port="test set results"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="concurrency:cross_validation" compatibility="8.2.000" expanded="true" height="145" name="CV DT" width="90" x="380" y="442">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="automatic"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="concurrency:parallel_decision_tree" compatibility="9.0.002" expanded="true" height="103" name="Decision Tree" width="90" x="179" y="34">
<parameter key="criterion" value="gain_ratio"/>
<parameter key="maximal_depth" value="20"/>
<parameter key="apply_pruning" value="true"/>
<parameter key="confidence" value="0.35"/>
<parameter key="apply_prepruning" value="true"/>
<parameter key="minimal_gain" value="0.1"/>
<parameter key="minimal_leaf_size" value="2"/>
<parameter key="minimal_size_for_split" value="4"/>
<parameter key="number_of_prepruning_alternatives" value="3"/>
</operator>
<connect from_port="training set" to_op="Decision Tree" to_port="training set"/>
<connect from_op="Decision Tree" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.0.002" expanded="true" height="82" name="Apply Model" width="90" x="112" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance" compatibility="9.0.002" expanded="true" height="82" name="Performance DT" width="90" x="313" y="34">
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="Apply Model" to_port="model"/>
<connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
<connect from_op="Apply Model" from_port="labelled data" to_op="Performance DT" to_port="labelled data"/>
<connect from_op="Performance DT" from_port="performance" to_port="performance 1"/>
<connect from_op="Performance DT" from_port="example set" to_port="test set results"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="concurrency:cross_validation" compatibility="8.2.000" expanded="true" height="145" name="CV LR" width="90" x="380" y="34">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="automatic"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="h2o:logistic_regression" compatibility="9.0.000" expanded="true" height="124" name="Logistic Regression" width="90" x="179" 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="0"/>
<parameter key="max_runtime_seconds" value="0"/>
</operator>
<connect from_port="training set" to_op="Logistic Regression" to_port="training set"/>
<connect from_op="Logistic Regression" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.0.002" expanded="true" height="82" name="Apply Model (3)" width="90" x="112" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance" compatibility="9.0.002" expanded="true" height="82" name="Performance LR" width="90" x="313" y="34">
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="Apply Model (3)" to_port="model"/>
<connect from_port="test set" to_op="Apply Model (3)" to_port="unlabelled data"/>
<connect from_op="Apply Model (3)" from_port="labelled data" to_op="Performance LR" to_port="labelled data"/>
<connect from_op="Performance LR" from_port="performance" to_port="performance 1"/>
<connect from_op="Performance LR" from_port="example set" to_port="test set results"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="apply_model" compatibility="9.0.002" expanded="true" height="82" name="DT Test" width="90" x="581" y="595">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="write_excel" compatibility="9.0.002" expanded="true" height="82" name="DT Write" width="90" x="916" y="595">
<parameter key="excel_file" value="C:\Users\zsherwin\Desktop\rapidminer\output_dt.xlsx"/>
<parameter key="file_format" value="xlsx"/>
<parameter key="encoding" value="SYSTEM"/>
<parameter key="sheet_name" value="RapidMiner Data"/>
<parameter key="date_format" value="yyyy-MM-dd HH:mm:ss"/>
<parameter key="number_format" value="#.0"/>
</operator>
<operator activated="true" class="jdbc_connectors:write_database" compatibility="9.0.002" expanded="true" height="68" name="DT Write Database" width="90" x="983" y="493">
<parameter key="define_connection" value="predefined"/>
<parameter key="connection" value="BERCMDS"/>
<parameter key="database_system" value="MySQL"/>
<parameter key="use_default_schema" value="true"/>
<parameter key="table_name" value="jrm.BER_RAPIDMINER_DT_OUTPUT_20180521"/>
<parameter key="overwrite_mode" value="none"/>
<parameter key="set_default_varchar_length" value="false"/>
<parameter key="default_varchar_length" value="128"/>
<parameter key="add_generated_primary_keys" value="false"/>
<parameter key="db_key_attribute_name" value="generated_primary_key"/>
<parameter key="batch_size" value="1"/>
</operator>
<operator activated="true" class="model_simulator:explain_predictions" compatibility="9.0.001" expanded="true" height="103" name="DT Explain Predictions" width="90" x="782" y="595">
<parameter key="maximal explaining attributes" value="3"/>
<parameter key="local sample size" value="500"/>
</operator>
<operator activated="true" class="apply_model" compatibility="9.0.002" expanded="true" height="82" name="DL Test" width="90" x="581" y="391">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="model_simulator:explain_predictions" compatibility="9.0.001" expanded="true" height="103" name="DL Explain Predictions" width="90" x="782" y="391">
<parameter key="maximal explaining attributes" value="3"/>
<parameter key="local sample size" value="500"/>
</operator>
<operator activated="true" class="write_excel" compatibility="9.0.002" expanded="true" height="82" name="DL Write" width="90" x="916" y="391">
<parameter key="excel_file" value="C:\Users\zsherwin\Desktop\rapidminer\output_dl.xlsx"/>
<parameter key="file_format" value="xlsx"/>
<parameter key="encoding" value="SYSTEM"/>
<parameter key="sheet_name" value="RapidMiner Data"/>
<parameter key="date_format" value="yyyy-MM-dd HH:mm:ss"/>
<parameter key="number_format" value="#.0"/>
</operator>
<operator activated="true" class="jdbc_connectors:write_database" compatibility="9.0.002" expanded="true" height="68" name="DL Write Database (2)" width="90" x="983" y="289">
<parameter key="define_connection" value="predefined"/>
<parameter key="connection" value="BERCMDS"/>
<parameter key="database_system" value="MySQL"/>
<parameter key="use_default_schema" value="true"/>
<parameter key="table_name" value="jrm.BER_RAPIDMINER_DL_OUTPUT_20180521"/>
<parameter key="overwrite_mode" value="none"/>
<parameter key="set_default_varchar_length" value="false"/>
<parameter key="default_varchar_length" value="128"/>
<parameter key="add_generated_primary_keys" value="false"/>
<parameter key="db_key_attribute_name" value="generated_primary_key"/>
<parameter key="batch_size" value="1"/>
</operator>
<operator activated="true" class="apply_model" compatibility="9.0.002" expanded="true" height="82" name="LR Test" width="90" x="581" y="187">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="model_simulator:explain_predictions" compatibility="9.0.001" expanded="true" height="103" name="LR Explain Predictions" width="90" x="782" y="187">
<parameter key="maximal explaining attributes" value="3"/>
<parameter key="local sample size" value="500"/>
</operator>
<operator activated="true" class="write_excel" compatibility="9.0.002" expanded="true" height="82" name="LR Write" width="90" x="916" y="187">
<parameter key="excel_file" value="C:\Users\zsherwin\Desktop\rapidminer\output_lr.xlsx"/>
<parameter key="file_format" value="xlsx"/>
<parameter key="encoding" value="SYSTEM"/>
<parameter key="sheet_name" value="RapidMiner Data"/>
<parameter key="date_format" value="yyyy-MM-dd HH:mm:ss"/>
<parameter key="number_format" value="#.0"/>
</operator>
<operator activated="true" class="jdbc_connectors:write_database" compatibility="9.0.002" expanded="true" height="68" name="LR Write Database (3)" width="90" x="983" y="85">
<parameter key="define_connection" value="predefined"/>
<parameter key="connection" value="BERCMDS"/>
<parameter key="database_system" value="MySQL"/>
<parameter key="use_default_schema" value="true"/>
<parameter key="table_name" value="jrm.BER_RAPIDMINER_LR_OUTPUT_20180521"/>
<parameter key="overwrite_mode" value="none"/>
<parameter key="set_default_varchar_length" value="false"/>
<parameter key="default_varchar_length" value="128"/>
<parameter key="add_generated_primary_keys" value="false"/>
<parameter key="db_key_attribute_name" value="generated_primary_key"/>
<parameter key="batch_size" value="1"/>
</operator>
<connect from_op="Retrieve 20180521 testing" from_port="output" to_op="Testing" to_port="input"/>
<connect from_op="Testing" from_port="output 1" to_op="DT Test" to_port="unlabelled data"/>
<connect from_op="Testing" from_port="output 2" to_op="DT Explain Predictions" to_port="test data"/>
<connect from_op="Testing" from_port="output 3" to_op="DL Test" to_port="unlabelled data"/>
<connect from_op="Testing" from_port="output 4" to_op="LR Test" to_port="unlabelled data"/>
<connect from_op="Testing" from_port="output 5" to_op="DL Explain Predictions" to_port="test data"/>
<connect from_op="Testing" from_port="output 6" to_op="LR Explain Predictions" to_port="test data"/>
<connect from_op="Retrieve 20180521 training" from_port="output" to_op="Training" to_port="input"/>
<connect from_op="Training" from_port="output 1" to_op="CV LR" to_port="example set"/>
<connect from_op="Training" from_port="output 2" to_op="DL Explain Predictions" to_port="training data"/>
<connect from_op="Training" from_port="output 3" to_op="LR Explain Predictions" to_port="training data"/>
<connect from_op="Training" from_port="output 4" to_op="CV DT" to_port="example set"/>
<connect from_op="Training" from_port="output 5" to_op="CV DL" to_port="example set"/>
<connect from_op="CV DL" from_port="model" to_op="DL Test" to_port="model"/>
<connect from_op="CV DL" from_port="performance 1" to_port="result 11"/>
<connect from_op="CV DT" from_port="model" to_op="DT Test" to_port="model"/>
<connect from_op="CV DT" from_port="example set" to_op="DT Explain Predictions" to_port="training data"/>
<connect from_op="CV DT" from_port="performance 1" to_port="result 10"/>
<connect from_op="CV LR" from_port="model" to_op="LR Test" to_port="model"/>
<connect from_op="CV LR" from_port="performance 1" to_port="result 12"/>
<connect from_op="DT Test" from_port="labelled data" to_op="DT Write" to_port="input"/>
<connect from_op="DT Test" from_port="model" to_op="DT Explain Predictions" to_port="model"/>
<connect from_op="DT Write" from_port="through" to_op="DT Write Database" to_port="input"/>
<connect from_op="DT Write Database" from_port="through" to_port="result 3"/>
<connect from_op="DT Explain Predictions" from_port="visualization output" to_port="result 4"/>
<connect from_op="DT Explain Predictions" from_port="importances output" to_port="result 5"/>
<connect from_op="DL Test" from_port="labelled data" to_op="DL Write" to_port="input"/>
<connect from_op="DL Test" from_port="model" to_op="DL Explain Predictions" to_port="model"/>
<connect from_op="DL Explain Predictions" from_port="visualization output" to_port="result 6"/>
<connect from_op="DL Explain Predictions" from_port="importances output" to_port="result 7"/>
<connect from_op="DL Write" from_port="through" to_op="DL Write Database (2)" to_port="input"/>
<connect from_op="DL Write Database (2)" from_port="through" to_port="result 2"/>
<connect from_op="LR Test" from_port="labelled data" to_op="LR Write" to_port="input"/>
<connect from_op="LR Test" from_port="model" to_op="LR Explain Predictions" to_port="model"/>
<connect from_op="LR Explain Predictions" from_port="visualization output" to_port="result 8"/>
<connect from_op="LR Explain Predictions" from_port="importances output" to_port="result 9"/>
<connect from_op="LR Write" from_port="through" to_op="LR Write Database (3)" to_port="input"/>
<connect from_op="LR Write Database (3)" from_port="through" 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"/>
<portSpacing port="sink_result 6" spacing="0"/>
<portSpacing port="sink_result 7" spacing="0"/>
<portSpacing port="sink_result 8" spacing="0"/>
<portSpacing port="sink_result 9" spacing="0"/>
<portSpacing port="sink_result 10" spacing="0"/>
<portSpacing port="sink_result 11" spacing="0"/>
<portSpacing port="sink_result 12" spacing="0"/>
<portSpacing port="sink_result 13" spacing="0"/>
</process>
</operator>
</process>

Best Answer

  • Options
    sgenzersgenzer Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 Community Manager
    Solution Accepted

    yes thanks @mschmitz you beat me to it. :) If you open the titanic tutorial for that operator and connect the IMP output of the Explain Predictions operator, you will get a nice table where the last table is "importance":

     

    Screen Shot 2018-09-06 at 1.22.17 PM.png

     

    At this point you can either use Generate Attributes to create a new column that converts these to colors, or just use the Conditional Formatting feature in Excel.

     

    Hope that helps!


    Scott

     

    XML of Titanic tutorial with IMP port connected to output:

     

    <?xml version="1.0" encoding="UTF-8"?><process version="9.0.001">
    <context>
    <input/>
    <output/>
    <macros/>
    </context>
    <operator activated="true" class="process" compatibility="9.0.001" expanded="true" name="Process" origin="GENERATED_TUTORIAL">
    <process expanded="true">
    <operator activated="true" class="retrieve" compatibility="9.0.001" expanded="true" height="68" name="Retrieve Titanic Training" origin="GENERATED_TUTORIAL" width="90" x="45" y="34">
    <parameter key="repository_entry" value="//Samples/data/Titanic Training"/>
    </operator>
    <operator activated="true" class="naive_bayes" compatibility="9.0.001" expanded="true" height="82" name="Naive Bayes" origin="GENERATED_TUTORIAL" width="90" x="179" y="34"/>
    <operator activated="true" class="retrieve" compatibility="9.0.001" expanded="true" height="68" name="Retrieve Titanic Unlabeled" origin="GENERATED_TUTORIAL" width="90" x="179" y="136">
    <parameter key="repository_entry" value="//Samples/data/Titanic Unlabeled"/>
    </operator>
    <operator activated="true" class="model_simulator:explain_predictions" compatibility="9.0.001" expanded="true" height="103" name="Explain Predictions" origin="GENERATED_TUTORIAL" width="90" x="313" y="34"/>
    <connect from_op="Retrieve Titanic Training" from_port="output" to_op="Naive Bayes" to_port="training set"/>
    <connect from_op="Naive Bayes" from_port="model" to_op="Explain Predictions" to_port="model"/>
    <connect from_op="Naive Bayes" from_port="exampleSet" to_op="Explain Predictions" to_port="training data"/>
    <connect from_op="Retrieve Titanic Unlabeled" from_port="output" to_op="Explain Predictions" to_port="test data"/>
    <connect from_op="Explain Predictions" from_port="visualization output" to_port="result 1"/>
    <connect from_op="Explain Predictions" from_port="example set output" to_port="result 2"/>
    <connect from_op="Explain Predictions" from_port="importances output" to_port="result 3"/>
    <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"/>
    </process>
    </operator>
    </process>

Answers

  • Options
    MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,508 RM Data Scientist

    Hey,

     

    the IMP port has the information.

     

    BR,

    Martin

    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
  • Options
    zsherwinzsherwin Member Posts: 2 Contributor I

    Thank you both, very much!

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