Log data table error

mansourmansour Member Posts: 14 Contributor II
edited June 2019 in Help
Hi
What does this error mean? Getting from Log to data operator
there is no log data table (or none with the specified name) available
Regards.

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Answers

  • sgenzersgenzer 12Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 Community Manager
    can you please post your process XML?
  • mansourmansour Member Posts: 14 Contributor II
    <?xml version="1.0" encoding="UTF-8"?><process version="9.3.000">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="9.3.000" 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="split_data" compatibility="9.3.000" expanded="true" height="103" name="Split Data" width="90" x="447" y="34">
            <enumeration key="partitions">
              <parameter key="ratio" value="0.6"/>
              <parameter key="ratio" value="0.4"/>
            </enumeration>
            <parameter key="sampling_type" value="automatic"/>
            <parameter key="use_local_random_seed" value="false"/>
            <parameter key="local_random_seed" value="1992"/>
          </operator>
          <operator activated="true" class="vote" compatibility="9.3.000" expanded="true" height="68" name="Vote" width="90" x="648" y="34">
            <process expanded="true">
              <operator activated="true" class="stacking" compatibility="9.3.000" expanded="true" height="68" name="Stacking" width="90" x="112" y="34">
                <parameter key="keep_all_attributes" value="true"/>
                <process expanded="true">
                  <operator activated="true" class="support_vector_machine" compatibility="9.3.000" expanded="true" height="124" name="SVM" width="90" x="112" 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>
                  <operator activated="true" class="concurrency:parallel_decision_tree" compatibility="9.3.000" expanded="true" height="103" name="Decision Tree" width="90" x="112" y="238">
                    <parameter key="criterion" value="gain_ratio"/>
                    <parameter key="maximal_depth" value="10"/>
                    <parameter key="apply_pruning" value="true"/>
                    <parameter key="confidence" value="0.1"/>
                    <parameter key="apply_prepruning" value="true"/>
                    <parameter key="minimal_gain" value="0.01"/>
                    <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 1" to_op="SVM" to_port="training set"/>
                  <connect from_port="training set 2" to_op="Decision Tree" to_port="training set"/>
                  <connect from_op="SVM" from_port="model" to_port="base model 1"/>
                  <connect from_op="Decision Tree" from_port="model" to_port="base model 2"/>
                  <portSpacing port="source_training set 1" spacing="0"/>
                  <portSpacing port="source_training set 2" spacing="63"/>
                  <portSpacing port="source_training set 3" spacing="0"/>
                  <portSpacing port="sink_base model 1" spacing="0"/>
                  <portSpacing port="sink_base model 2" spacing="0"/>
                  <portSpacing port="sink_base model 3" spacing="0"/>
                </process>
                <process expanded="true">
                  <operator activated="true" class="h2o:deep_learning" compatibility="7.2.000" expanded="true" height="82" name="Deep Learning (2)" width="90" x="112" 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_"/>
                    <description align="center" color="transparent" colored="false" width="126">rect</description>
                  </operator>
                  <connect from_port="stacking examples" to_op="Deep Learning (2)" to_port="training set"/>
                  <connect from_op="Deep Learning (2)" from_port="model" to_port="stacking model"/>
                  <portSpacing port="source_stacking examples" spacing="0"/>
                  <portSpacing port="sink_stacking model" spacing="0"/>
                </process>
              </operator>
              <operator activated="true" class="stacking" compatibility="9.3.000" expanded="true" height="68" name="Stacking (2)" width="90" x="112" y="136">
                <parameter key="keep_all_attributes" value="true"/>
                <process expanded="true">
                  <operator activated="true" class="naive_bayes" compatibility="9.3.000" expanded="true" height="82" name="Naive Bayes (2)" width="90" x="112" y="34">
                    <parameter key="laplace_correction" value="true"/>
                  </operator>
                  <operator activated="true" class="concurrency:parallel_decision_tree" compatibility="9.3.000" expanded="true" height="103" name="Decision Tree (2)" width="90" x="112" y="187">
                    <parameter key="criterion" value="gain_ratio"/>
                    <parameter key="maximal_depth" value="10"/>
                    <parameter key="apply_pruning" value="true"/>
                    <parameter key="confidence" value="0.1"/>
                    <parameter key="apply_prepruning" value="true"/>
                    <parameter key="minimal_gain" value="0.01"/>
                    <parameter key="minimal_leaf_size" value="2"/>
                    <parameter key="minimal_size_for_split" value="4"/>
                    <parameter key="number_of_prepruning_alternatives" value="3"/>
                  </operator>
                  <operator activated="true" class="h2o:gradient_boosted_trees" compatibility="9.2.000" expanded="true" height="103" name="Gradient Boosted Trees" width="90" x="179" y="391">
                    <parameter key="number_of_trees" value="100"/>
                    <parameter key="reproducible" value="false"/>
                    <parameter key="maximum_number_of_threads" value="4"/>
                    <parameter key="use_local_random_seed" value="false"/>
                    <parameter key="local_random_seed" value="1992"/>
                    <parameter key="maximal_depth" value="10"/>
                    <parameter key="min_rows" value="10.0"/>
                    <parameter key="min_split_improvement" value="0.0"/>
                    <parameter key="number_of_bins" value="20"/>
                    <parameter key="learning_rate" value="0.01"/>
                    <parameter key="sample_rate" value="1.0"/>
                    <parameter key="distribution" 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="max_runtime_seconds" value="0"/>
                    <list key="expert_parameters"/>
                  </operator>
                  <operator activated="true" class="perceptron" compatibility="9.3.000" expanded="true" height="82" name="Perceptron (2)" width="90" x="179" y="544">
                    <parameter key="rounds" value="3"/>
                    <parameter key="learning_rate" value="0.05"/>
                  </operator>
                  <operator activated="true" class="neural_net" compatibility="9.3.000" expanded="true" height="82" name="Neural Net (2)" width="90" x="112" y="697">
                    <list key="hidden_layers"/>
                    <parameter key="training_cycles" value="200"/>
                    <parameter key="learning_rate" value="0.01"/>
                    <parameter key="momentum" value="0.9"/>
                    <parameter key="decay" value="false"/>
                    <parameter key="shuffle" value="true"/>
                    <parameter key="normalize" value="true"/>
                    <parameter key="error_epsilon" value="1.0E-4"/>
                    <parameter key="use_local_random_seed" value="false"/>
                    <parameter key="local_random_seed" value="1992"/>
                  </operator>
                  <operator activated="true" class="neural_net" compatibility="9.3.000" expanded="true" height="82" name="Neural Net (3)" width="90" x="380" y="544">
                    <list key="hidden_layers"/>
                    <parameter key="training_cycles" value="200"/>
                    <parameter key="learning_rate" value="0.01"/>
                    <parameter key="momentum" value="0.9"/>
                    <parameter key="decay" value="false"/>
                    <parameter key="shuffle" value="true"/>
                    <parameter key="normalize" value="true"/>
                    <parameter key="error_epsilon" value="1.0E-4"/>
                    <parameter key="use_local_random_seed" value="false"/>
                    <parameter key="local_random_seed" value="1992"/>
                  </operator>
                  <connect from_port="training set 1" to_op="Naive Bayes (2)" to_port="training set"/>
                  <connect from_port="training set 2" to_op="Decision Tree (2)" to_port="training set"/>
                  <connect from_port="training set 3" to_op="Gradient Boosted Trees" to_port="training set"/>
                  <connect from_port="training set 4" to_op="Neural Net (3)" to_port="training set"/>
                  <connect from_port="training set 5" to_op="Perceptron (2)" to_port="training set"/>
                  <connect from_port="training set 6" to_op="Neural Net (2)" to_port="training set"/>
                  <connect from_op="Naive Bayes (2)" from_port="model" to_port="base model 1"/>
                  <connect from_op="Decision Tree (2)" from_port="model" to_port="base model 2"/>
                  <connect from_op="Gradient Boosted Trees" from_port="model" to_port="base model 3"/>
                  <connect from_op="Perceptron (2)" from_port="model" to_port="base model 6"/>
                  <connect from_op="Neural Net (2)" from_port="model" to_port="base model 4"/>
                  <connect from_op="Neural Net (3)" from_port="model" to_port="base model 5"/>
                  <portSpacing port="source_training set 1" spacing="0"/>
                  <portSpacing port="source_training set 2" spacing="0"/>
                  <portSpacing port="source_training set 3" spacing="0"/>
                  <portSpacing port="source_training set 4" spacing="0"/>
                  <portSpacing port="source_training set 5" spacing="0"/>
                  <portSpacing port="source_training set 6" spacing="0"/>
                  <portSpacing port="source_training set 7" spacing="0"/>
                  <portSpacing port="sink_base model 1" spacing="0"/>
                  <portSpacing port="sink_base model 2" spacing="0"/>
                  <portSpacing port="sink_base model 3" spacing="0"/>
                  <portSpacing port="sink_base model 4" spacing="0"/>
                  <portSpacing port="sink_base model 5" spacing="0"/>
                  <portSpacing port="sink_base model 6" spacing="0"/>
                  <portSpacing port="sink_base model 7" spacing="0"/>
                </process>
                <process expanded="true">
                  <operator activated="true" class="h2o:deep_learning" compatibility="7.2.000" expanded="true" height="82" name="Deep Learning (3)" width="90" x="112" 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_"/>
                    <description align="center" color="transparent" colored="false" width="126">rect</description>
                  </operator>
                  <connect from_port="stacking examples" to_op="Deep Learning (3)" to_port="training set"/>
                  <connect from_op="Deep Learning (3)" from_port="model" to_port="stacking model"/>
                  <portSpacing port="source_stacking examples" spacing="0"/>
                  <portSpacing port="sink_stacking model" spacing="0"/>
                </process>
              </operator>
              <connect from_port="training set 1" to_op="Stacking" to_port="training set"/>
              <connect from_port="training set 2" to_op="Stacking (2)" to_port="training set"/>
              <connect from_op="Stacking" from_port="model" to_port="base model 1"/>
              <connect from_op="Stacking (2)" from_port="model" to_port="base model 2"/>
              <portSpacing port="source_training set 1" spacing="0"/>
              <portSpacing port="source_training set 2" spacing="0"/>
              <portSpacing port="source_training set 3" spacing="0"/>
              <portSpacing port="source_training set 4" spacing="0"/>
              <portSpacing port="sink_base model 1" spacing="0"/>
              <portSpacing port="sink_base model 2" spacing="0"/>
              <portSpacing port="sink_base model 3" spacing="0"/>
              <portSpacing port="sink_base model 4" spacing="0"/>
            </process>
          </operator>
          <operator activated="true" breakpoints="after" class="multiply" compatibility="9.3.000" expanded="true" height="103" name="Multiply (5)" width="90" x="782" y="34"/>
          <operator activated="true" class="apply_model" compatibility="9.3.000" expanded="true" height="82" name="Apply Model (2)" width="90" x="916" y="85">
            <list key="application_parameters"/>
            <parameter key="create_view" value="false"/>
          </operator>
          <operator activated="true" class="performance_classification" compatibility="9.3.000" expanded="true" height="82" name="P Fold 1" width="90" x="1050" y="85">
            <parameter key="main_criterion" value="accuracy"/>
            <parameter key="accuracy" value="true"/>
            <parameter key="classification_error" value="true"/>
            <parameter key="kappa" value="true"/>
            <parameter key="weighted_mean_recall" value="true"/>
            <parameter key="weighted_mean_precision" value="true"/>
            <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="false"/>
            <parameter key="root_relative_squared_error" value="false"/>
            <parameter key="squared_error" value="true"/>
            <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" breakpoints="after" class="multiply" compatibility="9.3.000" expanded="true" height="103" name="Multiply (2)" width="90" x="1184" y="136"/>
          <operator activated="true" class="split_data" compatibility="9.3.000" expanded="true" height="103" name="Split Data (2)" width="90" x="447" y="238">
            <enumeration key="partitions">
              <parameter key="ratio" value="0.6"/>
              <parameter key="ratio" value="0.4"/>
            </enumeration>
            <parameter key="sampling_type" value="automatic"/>
            <parameter key="use_local_random_seed" value="false"/>
            <parameter key="local_random_seed" value="1992"/>
          </operator>
          <operator activated="true" class="vote" compatibility="9.3.000" expanded="true" height="68" name="Vote (2)" width="90" x="648" y="187">
            <process expanded="true">
              <operator activated="true" class="stacking" compatibility="9.3.000" expanded="true" height="68" name="Stacking (4)" width="90" x="112" y="34">
                <parameter key="keep_all_attributes" value="true"/>
                <process expanded="true">
                  <operator activated="true" class="support_vector_machine" compatibility="9.3.000" expanded="true" height="124" name="SVM (2)" width="90" x="112" 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>
                  <operator activated="true" class="concurrency:parallel_decision_tree" compatibility="9.3.000" expanded="true" height="103" name="Decision Tree (4)" width="90" x="246" y="187">
                    <parameter key="criterion" value="gain_ratio"/>
                    <parameter key="maximal_depth" value="10"/>
                    <parameter key="apply_pruning" value="true"/>
                    <parameter key="confidence" value="0.1"/>
                    <parameter key="apply_prepruning" value="true"/>
                    <parameter key="minimal_gain" value="0.01"/>
                    <parameter key="minimal_leaf_size" value="2"/>
                    <parameter key="minimal_size_for_split" value="4"/>
                    <parameter key="number_of_prepruning_alternatives" value="3"/>
                  </operator>
                  <operator activated="true" class="naive_bayes" compatibility="9.3.000" expanded="true" height="82" name="Naive Bayes" width="90" x="112" y="289">
                    <parameter key="laplace_correction" value="true"/>
                  </operator>
                  <operator activated="true" class="h2o:gradient_boosted_trees" compatibility="9.2.000" expanded="true" height="103" name="Gradient Boosted Trees (2)" width="90" x="45" y="442">
                    <parameter key="number_of_trees" value="100"/>
                    <parameter key="reproducible" value="false"/>
                    <parameter key="maximum_number_of_threads" value="4"/>
                    <parameter key="use_local_random_seed" value="false"/>
                    <parameter key="local_random_seed" value="1992"/>
                    <parameter key="maximal_depth" value="10"/>
                    <parameter key="min_rows" value="10.0"/>
                    <parameter key="min_split_improvement" value="0.0"/>
                    <parameter key="number_of_bins" value="20"/>
                    <parameter key="learning_rate" value="0.01"/>
                    <parameter key="sample_rate" value="1.0"/>
                    <parameter key="distribution" 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="max_runtime_seconds" value="0"/>
                    <list key="expert_parameters"/>
                  </operator>
                  <operator activated="true" class="perceptron" compatibility="9.3.000" expanded="true" height="82" name="Perceptron (3)" width="90" x="313" y="544">
                    <parameter key="rounds" value="3"/>
                    <parameter key="learning_rate" value="0.05"/>
                  </operator>
                  <operator activated="true" class="neural_net" compatibility="9.3.000" expanded="true" height="82" name="Neural Net (5)" width="90" x="179" y="646">
                    <list key="hidden_layers"/>
                    <parameter key="training_cycles" value="200"/>
                    <parameter key="learning_rate" value="0.01"/>
                    <parameter key="momentum" value="0.9"/>
                    <parameter key="decay" value="false"/>
                    <parameter key="shuffle" value="true"/>
                    <parameter key="normalize" value="true"/>
                    <parameter key="error_epsilon" value="1.0E-4"/>
                    <parameter key="use_local_random_seed" value="false"/>
                    <parameter key="local_random_seed" value="1992"/>
                 
  • mansourmansour Member Posts: 14 Contributor II
     </operator>
                  <operator activated="true" class="h2o:deep_learning" compatibility="9.2.000" expanded="true" height="82" name="Deep Learning" width="90" x="112" y="799">
                    <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 1" to_op="SVM (2)" to_port="training set"/>
                  <connect from_port="training set 2" to_op="Decision Tree (4)" to_port="training set"/>
                  <connect from_port="training set 3" to_op="Naive Bayes" to_port="training set"/>
                  <connect from_port="training set 4" to_op="Gradient Boosted Trees (2)" to_port="training set"/>
                  <connect from_port="training set 5" to_op="Perceptron (3)" to_port="training set"/>
                  <connect from_port="training set 6" to_op="Neural Net (5)" to_port="training set"/>
                  <connect from_port="training set 7" to_op="Deep Learning" to_port="training set"/>
                  <connect from_op="SVM (2)" from_port="model" to_port="base model 1"/>
                  <connect from_op="Decision Tree (4)" from_port="model" to_port="base model 2"/>
                  <connect from_op="Naive Bayes" from_port="model" to_port="base model 3"/>
                  <connect from_op="Gradient Boosted Trees (2)" from_port="model" to_port="base model 4"/>
                  <connect from_op="Perceptron (3)" from_port="model" to_port="base model 5"/>
                  <connect from_op="Neural Net (5)" from_port="model" to_port="base model 6"/>
                  <connect from_op="Deep Learning" from_port="model" to_port="base model 7"/>
                  <portSpacing port="source_training set 1" spacing="0"/>
                  <portSpacing port="source_training set 2" spacing="0"/>
                  <portSpacing port="source_training set 3" spacing="0"/>
                  <portSpacing port="source_training set 4" spacing="0"/>
                  <portSpacing port="source_training set 5" spacing="0"/>
                  <portSpacing port="source_training set 6" spacing="0"/>
                  <portSpacing port="source_training set 7" spacing="0"/>
                  <portSpacing port="source_training set 8" spacing="0"/>
                  <portSpacing port="sink_base model 1" spacing="0"/>
                  <portSpacing port="sink_base model 2" spacing="0"/>
                  <portSpacing port="sink_base model 3" spacing="0"/>
                  <portSpacing port="sink_base model 4" spacing="0"/>
                  <portSpacing port="sink_base model 5" spacing="0"/>
                  <portSpacing port="sink_base model 6" spacing="0"/>
                  <portSpacing port="sink_base model 7" spacing="0"/>
                  <portSpacing port="sink_base model 8" spacing="0"/>
                </process>
                <process expanded="true">
                  <operator activated="true" class="h2o:deep_learning" compatibility="7.2.000" expanded="true" height="82" name="Deep Learning (5)" width="90" x="112" 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_"/>
                    <description align="center" color="transparent" colored="false" width="126">rect</description>
                  </operator>
                  <connect from_port="stacking examples" to_op="Deep Learning (5)" to_port="training set"/>
                  <connect from_op="Deep Learning (5)" from_port="model" to_port="stacking model"/>
                  <portSpacing port="source_stacking examples" spacing="0"/>
                  <portSpacing port="sink_stacking model" spacing="0"/>
                </process>
              </operator>
              <connect from_port="training set 1" to_op="Stacking (4)" to_port="training set"/>
              <connect from_op="Stacking (4)" from_port="model" to_port="base model 1"/>
              <portSpacing port="source_training set 1" spacing="0"/>
              <portSpacing port="source_training set 2" spacing="0"/>
              <portSpacing port="source_training set 3" spacing="0"/>
              <portSpacing port="sink_base model 1" spacing="0"/>
              <portSpacing port="sink_base model 2" spacing="0"/>
              <portSpacing port="sink_base model 3" spacing="0"/>
            </process>
          </operator>
          <operator activated="true" breakpoints="before" class="multiply" compatibility="9.3.000" expanded="true" height="103" name="Multiply (6)" width="90" x="782" y="238"/>
          <operator activated="true" class="apply_model" compatibility="9.3.000" expanded="true" height="82" name="Apply Model" width="90" x="916" y="238">
            <list key="application_parameters"/>
            <parameter key="create_view" value="false"/>
          </operator>
          <operator activated="true" class="performance_classification" compatibility="9.3.000" expanded="true" height="82" name="P Fold 2" width="90" x="1050" y="238">
            <parameter key="main_criterion" value="accuracy"/>
            <parameter key="accuracy" value="true"/>
            <parameter key="classification_error" value="true"/>
            <parameter key="kappa" value="true"/>
            <parameter key="weighted_mean_recall" value="true"/>
            <parameter key="weighted_mean_precision" value="true"/>
            <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="false"/>
            <parameter key="root_relative_squared_error" value="false"/>
            <parameter key="squared_error" value="true"/>
            <parameter key="correlation" value="true"/>
            <parameter key="squared_correlation" value="true"/>
            <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" breakpoints="after" class="multiply" compatibility="9.3.000" expanded="true" height="103" name="Multiply (3)" width="90" x="1184" y="289"/>
          <operator activated="true" class="split_data" compatibility="9.3.000" expanded="true" height="103" name="Split Data (3)" width="90" x="447" y="442">
            <enumeration key="partitions">
              <parameter key="ratio" value="0.6"/>
              <parameter key="ratio" value="0.4"/>
            </enumeration>
            <parameter key="sampling_type" value="automatic"/>
            <parameter key="use_local_random_seed" value="false"/>
            <parameter key="local_random_seed" value="1992"/>
          </operator>
          <operator activated="true" class="vote" compatibility="9.3.000" expanded="true" height="68" name="Vote (3)" width="90" x="648" y="391">
            <process expanded="true">
              <operator activated="true" class="stacking" compatibility="9.3.000" expanded="true" height="68" name="Stacking (5)" width="90" x="246" y="34">
                <parameter key="keep_all_attributes" value="true"/>
                <process expanded="true">
                  <operator activated="true" class="support_vector_machine" compatibility="9.3.000" expanded="true" height="124" name="SVM (4)" width="90" x="112" 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>
                  <operator activated="true" class="concurrency:parallel_decision_tree" compatibility="9.3.000" expanded="true" height="103" name="Decision Tree (5)" width="90" x="246" y="187">
                    <parameter key="criterion" value="gain_ratio"/>
                    <parameter key="maximal_depth" value="10"/>
                    <parameter key="apply_pruning" value="true"/>
                    <parameter key="confidence" value="0.1"/>
                    <parameter key="apply_prepruning" value="true"/>
                    <parameter key="minimal_gain" value="0.01"/>
                    <parameter key="minimal_leaf_size" value="2"/>
                    <parameter key="minimal_size_for_split" value="4"/>
                    <parameter key="number_of_prepruning_alternatives" value="3"/>
                  </operator>
                  <operator activated="true" class="naive_bayes" compatibility="9.3.000" expanded="true" height="82" name="Naive Bayes (3)" width="90" x="112" y="289">
                    <parameter key="laplace_correction" value="true"/>
                  </operator>
                  <operator activated="true" class="h2o:gradient_boosted_trees" compatibility="9.2.000" expanded="true" height="103" name="Gradient Boosted Trees (3)" width="90" x="45" y="442">
                    <parameter key="number_of_trees" value="100"/>
                    <parameter key="reproducible" value="false"/>
                    <parameter key="maximum_number_of_threads" value="4"/>
                    <parameter key="use_local_random_seed" value="false"/>
                    <parameter key="local_random_seed" value="1992"/>
                    <parameter key="maximal_depth" value="10"/>
                    <parameter key="min_rows" value="10.0"/>
                    <parameter key="min_split_improvement" value="0.0"/>
                    <parameter key="number_of_bins" value="20"/>
                    <parameter key="learning_rate" value="0.01"/>
                    <parameter key="sample_rate" value="1.0"/>
                    <parameter key="distribution" 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="max_runtime_seconds" value="0"/>
                    <list key="expert_parameters"/>
                  </operator>
                  <operator activated="true" class="perceptron" compatibility="9.3.000" expanded="true" height="82" name="Perceptron" width="90" x="313" y="544">
                    <parameter key="rounds" value="3"/>
                    <parameter key="learning_rate" value="0.05"/>
                  </operator>
                 
  • mansourmansour Member Posts: 14 Contributor II
     <operator activated="true" class="neural_net" compatibility="9.3.000" expanded="true" height="82" name="Neural Net" width="90" x="179" y="646">
                    <list key="hidden_layers"/>
                    <parameter key="training_cycles" value="200"/>
                    <parameter key="learning_rate" value="0.01"/>
                    <parameter key="momentum" value="0.9"/>
                    <parameter key="decay" value="false"/>
                    <parameter key="shuffle" value="true"/>
                    <parameter key="normalize" value="true"/>
                    <parameter key="error_epsilon" value="1.0E-4"/>
                    <parameter key="use_local_random_seed" value="false"/>
                    <parameter key="local_random_seed" value="1992"/>
                  </operator>
                  <operator activated="true" class="h2o:deep_learning" compatibility="9.2.000" expanded="true" height="82" name="Deep Learning (4)" width="90" x="112" y="799">
                    <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 1" to_op="SVM (4)" to_port="training set"/>
                  <connect from_port="training set 2" to_op="Decision Tree (5)" to_port="training set"/>
                  <connect from_port="training set 3" to_op="Naive Bayes (3)" to_port="training set"/>
                  <connect from_port="training set 4" to_op="Gradient Boosted Trees (3)" to_port="training set"/>
                  <connect from_port="training set 5" to_op="Perceptron" to_port="training set"/>
                  <connect from_port="training set 6" to_op="Neural Net" to_port="training set"/>
                  <connect from_port="training set 7" to_op="Deep Learning (4)" to_port="training set"/>
                  <connect from_op="SVM (4)" from_port="model" to_port="base model 1"/>
                  <connect from_op="Decision Tree (5)" from_port="model" to_port="base model 2"/>
                  <connect from_op="Naive Bayes (3)" from_port="model" to_port="base model 3"/>
                  <connect from_op="Gradient Boosted Trees (3)" from_port="model" to_port="base model 4"/>
                  <connect from_op="Perceptron" from_port="model" to_port="base model 5"/>
                  <connect from_op="Neural Net" from_port="model" to_port="base model 6"/>
                  <connect from_op="Deep Learning (4)" from_port="model" to_port="base model 7"/>
                  <portSpacing port="source_training set 1" spacing="0"/>
                  <portSpacing port="source_training set 2" spacing="0"/>
                  <portSpacing port="source_training set 3" spacing="0"/>
                  <portSpacing port="source_training set 4" spacing="0"/>
                  <portSpacing port="source_training set 5" spacing="0"/>
                  <portSpacing port="source_training set 6" spacing="0"/>
                  <portSpacing port="source_training set 7" spacing="0"/>
                  <portSpacing port="source_training set 8" spacing="0"/>
                  <portSpacing port="sink_base model 1" spacing="0"/>
                  <portSpacing port="sink_base model 2" spacing="0"/>
                  <portSpacing port="sink_base model 3" spacing="0"/>
                  <portSpacing port="sink_base model 4" spacing="0"/>
                  <portSpacing port="sink_base model 5" spacing="0"/>
                  <portSpacing port="sink_base model 6" spacing="0"/>
                  <portSpacing port="sink_base model 7" spacing="0"/>
                  <portSpacing port="sink_base model 8" spacing="0"/>
                </process>
                <process expanded="true">
                  <operator activated="true" class="h2o:deep_learning" compatibility="7.2.000" expanded="true" height="82" name="Deep Learning (6)" width="90" x="112" 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_"/>
                    <description align="center" color="transparent" colored="false" width="126">rect</description>
                  </operator>
                  <connect from_port="stacking examples" to_op="Deep Learning (6)" to_port="training set"/>
                  <connect from_op="Deep Learning (6)" from_port="model" to_port="stacking model"/>
                  <portSpacing port="source_stacking examples" spacing="0"/>
                  <portSpacing port="sink_stacking model" spacing="0"/>
                </process>
              </operator>
              <connect from_port="training set 1" to_op="Stacking (5)" to_port="training set"/>
              <connect from_op="Stacking (5)" from_port="model" to_port="base model 1"/>
              <portSpacing port="source_training set 1" spacing="0"/>
              <portSpacing port="source_training set 2" spacing="0"/>
              <portSpacing port="sink_base model 1" spacing="0"/>
              <portSpacing port="sink_base model 2" spacing="0"/>
            </process>
          </operator>
          <operator activated="true" breakpoints="after" class="multiply" compatibility="9.3.000" expanded="true" height="103" name="Multiply (7)" width="90" x="782" y="442"/>
          <operator activated="true" class="apply_model" compatibility="9.3.000" expanded="true" height="82" name="Apply Model (3)" width="90" x="916" y="442">
            <list key="application_parameters"/>
            <parameter key="create_view" value="false"/>
          </operator>
          <operator activated="true" class="performance_classification" compatibility="9.3.000" expanded="true" height="82" name="P Fold 3" width="90" x="1050" y="442">
            <parameter key="main_criterion" value="accuracy"/>
            <parameter key="accuracy" value="true"/>
            <parameter key="classification_error" value="true"/>
            <parameter key="kappa" value="true"/>
            <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="false"/>
            <parameter key="root_relative_squared_error" value="false"/>
            <parameter key="squared_error" value="true"/>
            <parameter key="correlation" value="true"/>
            <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" breakpoints="after" class="multiply" compatibility="9.3.000" expanded="true" height="103" name="Multiply (4)" width="90" x="1184" y="493"/>
          <operator activated="true" breakpoints="after" class="log" compatibility="9.3.000" expanded="true" height="124" name="Log" width="90" x="1318" y="646">
            <parameter key="filename" value="C:\Users\manij\Documents\Log.log"/>
            <list key="log">
              <parameter key="P Fold 1 Accuracy" value="operator.P Fold 1.value.accuracy"/>
              <parameter key="P Fold 1 Performance" value="operator.P Fold 1.value.performance"/>
              <parameter key="P Fold 1 RMSE" value="operator.P Fold 1.value.root_mean_squared_error"/>
              <parameter key="P Fold 2 Accuracy" value="operator.P Fold 2.value.accuracy"/>
              <parameter key="P Fold 2 Performance" value="operator.P Fold 2.value.performance"/>
              <parameter key="P Fold 2 RMSE" value="operator.P Fold 2.value.root_mean_squared_error"/>
              <parameter key="P Fold 3 Accuracy" value="operator.P Fold 3.value.accuracy"/>
              <parameter key="P Fold 3 Performance" value="operator.P Fold 3.value.performance"/>
              <parameter key="P Fold 3 RMSE" value="operator.P Fold 3.value.root_mean_squared_error"/>
            </list>
            <parameter key="sorting_type" value="none"/>
            <parameter key="sorting_k" value="100"/>
            <parameter key="persistent" value="false"/>
          </operator>
          <operator activated="true" class="log_to_data" compatibility="9.3.000" expanded="true" height="145" name="Log to Data" width="90" x="1452" y="646">
            <parameter key="log_name" value="Log to Data"/>
          </operator>
          <operator activated="true" class="write_csv" compatibility="9.3.000" expanded="true" height="82" name="Write CSV" width="90" x="1519" y="187">
            <parameter key="csv_file" value="D:\Mansour\Cloudstor\MEQ\mansour feature selection boosting bagging voting 16 June 2019\voting stacking\Results Stacking inside Voting Run on 40%\Manijeh Data Stacking voting Performances.csv"/>
            <parameter key="column_separator" value=";"/>
            <parameter key="write_attribute_names" value="true"/>
            <parameter key="quote_nominal_values" value="true"/>
            <parameter key="format_date_attributes" value="true"/>
            <parameter key="append_to_file" value="false"/>
            <parameter key="encoding" value="SYSTEM"/>
          </operator>
          <connect from_op="Split Data" from_port="partition 1" to_op="Vote" to_port="training set"/>
          <connect from_op="Split Data" from_port="partition 2" to_op="Apply Model (2)" to_port="unlabelled data"/>
          <connect from_op="Vote" from_port="model" to_op="Multiply (5)" to_port="input"/>
          <connect from_op="Multiply (5)" from_port="output 1" to_op="Apply Model (2)" to_port="model"/>
          <connect from_op="Multiply (5)" from_port="output 2" to_port="result 2"/>
          <connect from_op="Apply Model (2)" from_port="labelled data" to_op="P Fold 1" to_port="labelled data"/>
          <connect from_op="Apply Model (2)" from_port="model" to_port="result 1"/>
          <connect from_op="P Fold 1" from_port="performance" to_op="Multiply (2)" to_port="input"/>
          <connect from_op="Multiply (2)" from_port="output 1" to_op="Log" to_port="through 1"/>
          <connect from_op="Multiply (2)" from_port="output 2" to_port="result 6"/>
          <connect from_op="Split Data (2)" from_port="partition 1" to_op="Vote (2)" to_port="training set"/>
          <connect from_op="Split Data (2)" from_port="partition 2" to_op="Apply Model" to_port="unlabelled data"/>
          <connect from_op="Vote (2)" from_port="model" to_op="Multiply (6)" to_port="input"/>
          <connect from_op="Multiply (6)" from_port="output 1" to_op="Apply Model" to_port="model"/>
          <connect from_op="Multiply (6)" from_port="output 2" to_port="result 3"/>
          <connect from_op="Apply Model" from_port="labelled data" to_op="P Fold 2" to_port="labelled data"/>
          <connect from_op="P Fold 2" from_port="performance" to_op="Multiply (3)" to_port="input"/>
          <connect from_op="Multiply (3)" from_port="output 1" to_op="Log" to_port="through 2"/>
          <connect from_op="Multiply (3)" from_port="output 2" to_port="result 7"/>
          <connect from_op="Split Data (3)" from_port="partition 1" to_op="Vote (3)" to_port="training set"/>
          <connect from_op="Split Data (3)" from_port="partition 2" to_op="Apply Model (3)" to_port="unlabelled data"/>
          <connect from_op="Vote (3)" from_port="model" to_op="Multiply (7)" to_port="input"/>
          <connect from_op="Multiply (7)" from_port="output 1" to_op="Apply Model (3)" to_port="model"/>
          <connect from_op="Multiply (7)" from_port="output 2" to_port="result 4"/>
          <connect from_op="Apply Model (3)" from_port="labelled data" to_op="P Fold 3" to_port="labelled data"/>
          <connect from_op="P Fold 3" from_port="performance" to_op="Multiply (4)" to_port="input"/>
          <connect from_op="Multiply (4)" from_port="output 1" to_op="Log" to_port="through 3"/>
          <connect from_op="Multiply (4)" from_port="output 2" to_port="result 8"/>
          <connect from_op="Log" from_port="through 1" to_op="Log to Data" to_port="through 1"/>
          <connect from_op="Log" from_port="through 2" to_op="Log to Data" to_port="through 2"/>
          <connect from_op="Log" from_port="through 3" to_op="Log to Data" to_port="through 3"/>
          <connect from_op="Log to Data" from_port="exampleSet" to_op="Write CSV" to_port="input"/>
          <connect from_op="Write CSV" from_port="through" to_port="result 5"/>
          <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="147"/>
          <portSpacing port="sink_result 7" spacing="0"/>
          <portSpacing port="sink_result 8" spacing="0"/>
          <portSpacing port="sink_result 9" spacing="0"/>
        </process>
      </operator>
    </process>

  • mansourmansour Member Posts: 14 Contributor II
    Sorry had to split it; too long for one post

  • sgenzersgenzer 12Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 Community Manager
    hmm ok @mansour so yes it have been easier if you had just attached the .rmp file :wink:

    I don't have any inputs here so I cannot run your process. Your process starts with Split Data operators which are left empty on the input side:



    Scott

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