Log data table error

mansour
New Altair Community Member
Answers
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can you please post your process XML?0
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<?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"/>0
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</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>0
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<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>0
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Sorry had to split it; too long for one post
0