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Logging Best Parameters and Learned Weights from Cross Validation

IUH_86IUH_86 Member Posts: 4 Learner I
edited May 2023 in Help
Hi!
Is there a way to obtain the best parameter combination output from cross-validation operator? After running the cross validation on the train set, I need to log the best parameters and the weights for the features learned by the model. What operators should I use for this? 
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Answers

  • ceaperezceaperez Member Posts: 541 Unicorn
    Hi @IUH_86, 

    have you try to connect the mod port to the res port from the Cross Validation operator?

    There you have acess to the final model. 

    Best,

    Cesar
  • IUH_86IUH_86 Member Posts: 4 Learner I
    Hi @ceaperez,

    Thanks for the helpful answer. But I am doing this iteratively, so I must log the feature weights and model parameters at each iteration. I cannot find a suitable option in the log operator to do this.
  • ceaperezceaperez Member Posts: 541 Unicorn
    Hi @IUH_86, 

    are you trying with log operator?

    Best, 

    Cesar 
  • IUH_86IUH_86 Member Posts: 4 Learner I
    Hi @ceaperez,

    Yes, I am trying the log operator. But I cannot figure out the parameter options in the log operator to retrieve the best model parameters and feature weights from cross-validation. Do you have any idea how to do it?
  • ceaperezceaperez Member Posts: 541 Unicorn
    Hi @IUH_86,

    can you share your process file ? 

    Cheers
  • IUH_86IUH_86 Member Posts: 4 Learner I
    Hi @ceaperez,

    Below is the process file. I must get weights for each attribute as columns for each window in the log file. 

    <?xml version="1.0" encoding="UTF-8"?><process version="10.1.002">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="10.1.002" 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="10.1.002" expanded="true" height="68" name="Retrieve Weighting" width="90" x="45" y="34">
            <parameter key="repository_entry" value="//Samples/data/Weighting"/>
          </operator>
          <operator activated="true" class="filter_example_range" compatibility="10.1.002" expanded="true" height="82" name="Filter Example Range" width="90" x="179" y="34">
            <parameter key="first_example" value="1"/>
            <parameter key="last_example" value="302"/>
            <parameter key="invert_filter" value="false"/>
          </operator>
          <operator activated="true" class="blending:set_role" compatibility="10.1.002" expanded="true" height="82" name="Set Role" width="90" x="313" y="34">
            <list key="set_roles">
              <parameter key="weighting.dat (7)" value="label"/>
            </list>
          </operator>
          <operator activated="true" class="time_series:sliding_window_validation" compatibility="10.1.000" expanded="true" height="145" name="Sliding Window Validation" width="90" x="447" y="34">
            <parameter key="has_indices" value="false"/>
            <parameter key="indices_attribute" value="Last Date in window"/>
            <parameter key="sort_time_series" value="false"/>
            <parameter key="expert_settings" value="false"/>
            <parameter key="unit" value="example based"/>
            <parameter key="windows_defined" value="from start"/>
            <parameter key="custom_start_point" value="5"/>
            <parameter key="custom_end_point" value="100"/>
            <parameter key="training_window_size" value="200"/>
            <parameter key="custom_start_time" value="2000-01-01 00:00:00"/>
            <parameter key="custom_end_time" value="2030-01-01 00:00:00"/>
            <parameter key="date_format" value="yyyy-MM-dd HH:mm:ss"/>
            <parameter key="training_window_size_time" value="1.Hours"/>
            <parameter key="windows_stop_definition" value="from next window start"/>
            <parameter key="training_window_start_attribute" value=""/>
            <parameter key="training_window_stop_attribute" value=""/>
            <parameter key="no_overlapping_windows" value="false"/>
            <parameter key="step_size" value="1"/>
            <parameter key="step_size_time" value="1.Minutes"/>
            <parameter key="test_window_size" value="100"/>
            <parameter key="test_window_size_time" value="1.Hours"/>
            <parameter key="test_window_start_attribute" value=""/>
            <parameter key="test_window_stop_attribute" value=""/>
            <parameter key="empty_window_handling" value="add empty exampleset"/>
            <parameter key="enable_parallel_execution" value="true"/>
            <process expanded="true">
              <operator activated="true" class="concurrency:optimize_parameters_grid" compatibility="10.1.002" expanded="true" height="124" name="Optimize Parameters (Grid)" width="90" x="112" y="34">
                <list key="parameters">
                  <parameter key="SVM.kernel_type" value="dot,radial,polynomial"/>
                </list>
                <parameter key="error_handling" value="fail on error"/>
                <parameter key="log_performance" value="true"/>
                <parameter key="log_all_criteria" value="true"/>
                <parameter key="synchronize" value="false"/>
                <parameter key="enable_parallel_execution" value="true"/>
                <process expanded="true">
                  <operator activated="true" class="concurrency:cross_validation" compatibility="10.1.002" expanded="true" height="145" name="Cross Validation" width="90" x="246" y="34">
                    <parameter key="split_on_batch_attribute" value="false"/>
                    <parameter key="leave_one_out" value="false"/>
                    <parameter key="number_of_folds" value="5"/>
                    <parameter key="sampling_type" value="linear sampling"/>
                    <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="support_vector_machine" compatibility="10.1.002" expanded="true" height="124" name="SVM" width="90" x="179" y="34">
                        <parameter key="kernel_type" value="dot"/>
                        <parameter key="kernel_gamma" value="1.0"/>
                        <parameter key="kernel_sigma1" value="1.0"/>
                        <parameter key="kernel_sigma2" value="0.0"/>
                        <parameter key="kernel_sigma3" value="2.0"/>
                        <parameter key="kernel_shift" value="1.0"/>
                        <parameter key="kernel_degree" value="2.0"/>
                        <parameter key="kernel_a" value="1.0"/>
                        <parameter key="kernel_b" value="0.0"/>
                        <parameter key="kernel_cache" value="200"/>
                        <parameter key="C" value="0.0"/>
                        <parameter key="convergence_epsilon" value="0.001"/>
                        <parameter key="max_iterations" value="100000"/>
                        <parameter key="scale" value="true"/>
                        <parameter key="calculate_weights" value="true"/>
                        <parameter key="return_optimization_performance" value="true"/>
                        <parameter key="L_pos" value="1.0"/>
                        <parameter key="L_neg" value="1.0"/>
                        <parameter key="epsilon" value="0.0"/>
                        <parameter key="epsilon_plus" value="0.0"/>
                        <parameter key="epsilon_minus" value="0.0"/>
                        <parameter key="balance_cost" value="false"/>
                        <parameter key="quadratic_loss_pos" value="false"/>
                        <parameter key="quadratic_loss_neg" value="false"/>
                        <parameter key="estimate_performance" value="false"/>
                      </operator>
                      <connect from_port="training set" to_op="SVM" to_port="training set"/>
                      <connect from_op="SVM" from_port="model" to_port="model"/>
                      <connect from_op="SVM" from_port="estimated performance" to_port="through 1"/>
                      <connect from_op="SVM" from_port="weights" to_port="through 2"/>
                      <portSpacing port="source_training set" spacing="0"/>
                      <portSpacing port="sink_model" spacing="0"/>
                      <portSpacing port="sink_through 1" spacing="0"/>
                      <portSpacing port="sink_through 2" spacing="0"/>
                      <portSpacing port="sink_through 3" spacing="0"/>
                    </process>
                    <process expanded="true">
                      <operator activated="true" class="apply_model" compatibility="10.1.002" expanded="true" height="82" name="Apply Model (2)" width="90" x="112" y="34">
                        <list key="application_parameters"/>
                      </operator>
                      <operator activated="true" class="performance_classification" compatibility="10.1.002" expanded="true" height="82" name="Performance (2)" width="90" x="277" y="34">
                        <parameter key="main_criterion" value="root_mean_squared_error"/>
                        <parameter key="accuracy" value="true"/>
                        <parameter key="classification_error" value="false"/>
                        <parameter key="kappa" value="false"/>
                        <parameter key="weighted_mean_recall" value="false"/>
                        <parameter key="weighted_mean_precision" value="false"/>
                        <parameter key="spearman_rho" value="false"/>
                        <parameter key="kendall_tau" value="false"/>
                        <parameter key="absolute_error" value="false"/>
                        <parameter key="relative_error" value="false"/>
                        <parameter key="relative_error_lenient" value="false"/>
                        <parameter key="relative_error_strict" value="false"/>
                        <parameter key="normalized_absolute_error" value="false"/>
                        <parameter key="root_mean_squared_error" value="true"/>
                        <parameter key="root_relative_squared_error" value="false"/>
                        <parameter key="squared_error" value="false"/>
                        <parameter key="correlation" value="false"/>
                        <parameter key="squared_correlation" value="false"/>
                        <parameter key="cross-entropy" value="false"/>
                        <parameter key="margin" value="false"/>
                        <parameter key="soft_margin_loss" value="false"/>
                        <parameter key="logistic_loss" value="false"/>
                        <parameter key="skip_undefined_labels" value="true"/>
                        <parameter key="use_example_weights" value="true"/>
                        <list key="class_weights"/>
                      </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 (2)" to_port="labelled data"/>
                      <connect from_op="Performance (2)" from_port="performance" to_port="performance 1"/>
                      <connect from_op="Performance (2)" 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="source_through 2" spacing="0"/>
                      <portSpacing port="source_through 3" 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>
                  <connect from_port="input 1" to_op="Cross Validation" to_port="example set"/>
                  <connect from_op="Cross Validation" from_port="model" to_port="model"/>
                  <connect from_op="Cross Validation" from_port="performance 1" to_port="performance"/>
                  <portSpacing port="source_input 1" spacing="0"/>
                  <portSpacing port="source_input 2" spacing="0"/>
                  <portSpacing port="sink_performance" spacing="0"/>
                  <portSpacing port="sink_model" spacing="0"/>
                  <portSpacing port="sink_output 1" spacing="0"/>
                </process>
              </operator>
              <connect from_port="training set" to_op="Optimize Parameters (Grid)" to_port="input 1"/>
              <connect from_op="Optimize Parameters (Grid)" from_port="model" to_port="model"/>
              <connect from_op="Optimize Parameters (Grid)" from_port="parameter set" to_port="through 1"/>
              <portSpacing port="source_training set" spacing="0"/>
              <portSpacing port="sink_model" spacing="0"/>
              <portSpacing port="sink_through 1" spacing="0"/>
              <portSpacing port="sink_through 2" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" class="apply_model" compatibility="10.1.002" expanded="true" height="82" name="Apply Model" width="90" x="112" y="34">
                <list key="application_parameters"/>
              </operator>
              <operator activated="true" class="performance_classification" compatibility="10.1.002" expanded="true" height="82" name="Performance" width="90" x="246" y="34">
                <parameter key="main_criterion" value="root_mean_squared_error"/>
                <parameter key="accuracy" value="true"/>
                <parameter key="classification_error" value="false"/>
                <parameter key="kappa" value="false"/>
                <parameter key="weighted_mean_recall" value="false"/>
                <parameter key="weighted_mean_precision" value="false"/>
                <parameter key="spearman_rho" value="false"/>
                <parameter key="kendall_tau" value="false"/>
                <parameter key="absolute_error" value="true"/>
                <parameter key="relative_error" value="true"/>
                <parameter key="relative_error_lenient" value="false"/>
                <parameter key="relative_error_strict" value="false"/>
                <parameter key="normalized_absolute_error" value="false"/>
                <parameter key="root_mean_squared_error" value="true"/>
                <parameter key="root_relative_squared_error" value="false"/>
                <parameter key="squared_error" value="false"/>
                <parameter key="correlation" value="false"/>
                <parameter key="squared_correlation" value="false"/>
                <parameter key="cross-entropy" value="false"/>
                <parameter key="margin" value="false"/>
                <parameter key="soft_margin_loss" value="false"/>
                <parameter key="logistic_loss" value="false"/>
                <parameter key="skip_undefined_labels" value="true"/>
                <parameter key="use_example_weights" value="true"/>
                <list key="class_weights"/>
              </operator>
              <operator activated="true" class="log" compatibility="10.1.002" expanded="true" height="82" name="Log" width="90" x="112" y="238">
                <list key="log">
                  <parameter key="SVM.kernel" value="operator.SVM.parameter.kernel_type"/>
                  <parameter key="Window Number" value="operator.Sliding Window Validation.value.looptime"/>
                  <parameter key="Performance" value="operator.Performance.value.accuracy"/>
                </list>
                <parameter key="sorting_type" value="none"/>
                <parameter key="sorting_k" value="100"/>
                <parameter key="persistent" value="false"/>
              </operator>
              <connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
              <connect from_port="model" to_op="Apply Model" to_port="model"/>
              <connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
              <connect from_op="Performance" from_port="performance" to_port="performance 1"/>
              <connect from_op="Performance" from_port="example set" to_port="test set results"/>
              <portSpacing port="source_test set" spacing="0"/>
              <portSpacing port="source_model" spacing="0"/>
              <portSpacing port="source_through 1" spacing="0"/>
              <portSpacing port="source_through 2" spacing="0"/>
              <portSpacing port="sink_test set results" spacing="0"/>
              <portSpacing port="sink_performance 1" spacing="0"/>
              <portSpacing port="sink_performance 2" spacing="0"/>
              <description align="center" color="yellow" colored="false" height="69" resized="false" width="126" x="72" y="125">Apply the best model on the test dataset</description>
              <description align="center" color="yellow" colored="false" height="93" resized="false" width="144" x="229" y="124">Collect performance measures for the current test set and the forecasted values</description>
            </process>
          </operator>
          <connect from_op="Retrieve Weighting" from_port="output" to_op="Filter Example Range" to_port="example set input"/>
          <connect from_op="Filter Example Range" 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="Sliding Window Validation" to_port="example set"/>
          <connect from_op="Sliding Window Validation" from_port="model" to_port="result 1"/>
          <connect from_op="Sliding Window Validation" from_port="test result set" to_port="result 2"/>
          <connect from_op="Sliding Window Validation" from_port="performance 1" 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>
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