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Model3.xml
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Model3.xml
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<?xml version="1.0" encoding="UTF-8"?><process version="9.10.001">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="9.4.000" expanded="true" name="Process" origin="GENERATED_TUTORIAL">
<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="productivity:execute_process" compatibility="9.10.001" expanded="true" height="103" name="Execute Process" width="90" x="45" y="187">
<parameter key="process_location" value="//Local Repository/Thesis/Data Preparation/FinalDatasetPreprocessingUniqueSubjectID"/>
<parameter key="use_input" value="true"/>
<parameter key="store_output" value="false"/>
<parameter key="propagate_metadata_recursively" value="true"/>
<parameter key="cache_process" value="true"/>
<list key="macros"/>
<parameter key="fail_for_unknown_macros" value="true"/>
</operator>
<operator activated="true" class="subprocess" compatibility="9.10.001" expanded="true" height="166" name="Training Data Preparation" width="90" x="179" y="85">
<process expanded="true">
<operator activated="true" class="remove_correlated_attributes" compatibility="9.10.001" expanded="true" height="82" name="Remove Correlated Attributes" origin="EXPORTED_TURBOPREP" width="90" x="45" y="34">
<parameter key="correlation" value="0.9"/>
<parameter key="filter_relation" value="greater"/>
<parameter key="attribute_order" value="original"/>
<parameter key="use_absolute_correlation" value="true"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<description align="center" color="transparent" colored="false" width="126">Remove columns with correlation > 0.900</description>
</operator>
<operator activated="true" class="subprocess" compatibility="9.10.001" expanded="true" height="103" name="Outlier elimination" width="90" x="179" y="34">
<process expanded="true">
<operator activated="true" class="normalize" compatibility="9.10.001" expanded="true" height="103" name="Normalize attributes" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
<parameter key="return_preprocessing_model" value="false"/>
<parameter key="create_view" value="false"/>
<parameter key="attribute_filter_type" value="all"/>
<parameter key="attribute" value="ID"/>
<parameter key="attributes" value=""/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="numeric"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="real"/>
<parameter key="block_type" value="value_series"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_series_end"/>
<parameter key="invert_selection" value="false"/>
<parameter key="include_special_attributes" value="false"/>
<parameter key="method" value="Z-transformation"/>
<parameter key="min" value="0.0"/>
<parameter key="max" value="1.0"/>
<parameter key="allow_negative_values" value="false"/>
<description align="center" color="transparent" colored="false" width="126">Standardize all columns.</description>
</operator>
<operator activated="true" class="anomalydetection:univariate_anomaly_detection" compatibility="3.3.000" expanded="true" height="82" name="Detect Outlier (Univariate)" width="90" x="179" y="34">
<parameter key="attribute_filter_type" value="all"/>
<parameter key="attribute" value="ID"/>
<parameter key="attributes" value=""/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="numeric"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="real"/>
<parameter key="block_type" value="value_series"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_series_end"/>
<parameter key="invert_selection" value="false"/>
<parameter key="include_special_attributes" value="false"/>
<parameter key="method" value="Histogram"/>
<parameter key="aggregation_method" value="Average"/>
<parameter key="show_individual_scores" value="false"/>
</operator>
<operator activated="true" class="anomalydetection:generate_anomaly_flag" compatibility="3.3.000" expanded="true" height="103" name="Generate Outlier Flag" width="90" x="313" y="34">
<parameter key="method" value="contamination"/>
<parameter key="define_score_column" value="true"/>
<parameter key="score_column" value="score"/>
<parameter key="contamination_threshold" value="0.001"/>
<parameter key="manual_threshold" value="1.0"/>
<parameter key="zscore_threshold" value="3.0"/>
</operator>
<operator activated="true" class="filter_examples" compatibility="9.10.001" expanded="true" height="103" name="Fliter out outliers" width="90" x="447" y="34">
<parameter key="parameter_expression" value=""/>
<parameter key="condition_class" value="custom_filters"/>
<parameter key="invert_filter" value="false"/>
<list key="filters_list">
<parameter key="filters_entry_key" value="outlier_flag.does_not_equal.Outlier"/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
<operator activated="true" class="select_attributes" compatibility="9.10.001" expanded="true" height="82" name="Select Attributes" width="90" x="648" y="34">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value="outlier_flag|score|hadm_id"/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="attribute_value"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="time"/>
<parameter key="block_type" value="attribute_block"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_matrix_row_start"/>
<parameter key="invert_selection" value="false"/>
<parameter key="include_special_attributes" value="true"/>
</operator>
<operator activated="true" class="concurrency:join" compatibility="9.10.001" expanded="true" height="82" name="Join" width="90" x="782" y="85">
<parameter key="remove_double_attributes" value="false"/>
<parameter key="join_type" value="inner"/>
<parameter key="use_id_attribute_as_key" value="true"/>
<list key="key_attributes">
<parameter key="ID" value="ID"/>
</list>
<parameter key="keep_both_join_attributes" value="false"/>
</operator>
<operator activated="true" class="select_attributes" compatibility="9.10.001" expanded="true" height="82" name="Clean ExampleSet" origin="EXPORTED_AUTOMODEL" width="90" x="916" y="85">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attribute" value="id"/>
<parameter key="attributes" value="outlier_flag|score"/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="attribute_value"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="time"/>
<parameter key="block_type" value="attribute_block"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_matrix_row_start"/>
<parameter key="invert_selection" value="true"/>
<parameter key="include_special_attributes" value="true"/>
<description align="center" color="transparent" colored="false" width="126">Remove outlier flag and score</description>
</operator>
<connect from_port="in 1" to_op="Normalize attributes" to_port="example set input"/>
<connect from_op="Normalize attributes" from_port="example set output" to_op="Detect Outlier (Univariate)" to_port="exa"/>
<connect from_op="Normalize attributes" from_port="original" to_op="Join" to_port="right"/>
<connect from_op="Detect Outlier (Univariate)" from_port="outlier" to_op="Generate Outlier Flag" to_port="example set"/>
<connect from_op="Generate Outlier Flag" from_port="example set" to_op="Fliter out outliers" to_port="example set input"/>
<connect from_op="Fliter out outliers" from_port="example set output" to_op="Select Attributes" to_port="example set input"/>
<connect from_op="Fliter out outliers" from_port="original" to_port="out 1"/>
<connect from_op="Select Attributes" from_port="example set output" to_op="Join" to_port="left"/>
<connect from_op="Join" from_port="join" to_op="Clean ExampleSet" to_port="example set input"/>
<connect from_op="Clean ExampleSet" from_port="example set output" to_port="out 2"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
<portSpacing port="sink_out 3" spacing="0"/>
</process>
</operator>
<operator activated="true" class="subprocess" compatibility="9.10.001" expanded="true" height="145" name="Auto FE" width="90" x="313" y="85">
<process expanded="true">
<operator activated="true" class="multiply" compatibility="9.10.001" expanded="true" height="103" name="Multiply Preprocessed dataset" width="90" x="45" y="34"/>
<operator activated="true" class="select_attributes" compatibility="9.10.001" expanded="true" height="82" name="Attribute Filtering" width="90" x="179" y="85">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attribute" value="scr_baseline"/>
<parameter key="attributes" value="AnionGap|Bicarbonate|UreaNitrogene|Creatinine (Baseline)"/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="attribute_value"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="time"/>
<parameter key="block_type" value="attribute_block"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_matrix_row_start"/>
<parameter key="invert_selection" value="true"/>
<parameter key="include_special_attributes" value="false"/>
</operator>
<operator activated="true" class="sample" compatibility="9.10.001" expanded="true" height="82" name="Sample down for FE" width="90" x="313" y="85">
<parameter key="sample" value="relative"/>
<parameter key="balance_data" value="false"/>
<parameter key="sample_size" value="100"/>
<parameter key="sample_ratio" value="0.05"/>
<parameter key="sample_probability" value="0.1"/>
<list key="sample_size_per_class"/>
<list key="sample_ratio_per_class">
<parameter key="ckd" value="0.1"/>
<parameter key="notckd" value="0.1"/>
</list>
<list key="sample_probability_per_class"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<operator activated="true" class="model_simulator:automatic_feature_engineering" compatibility="9.10.001" expanded="true" height="103" name="FE" width="90" x="447" y="85">
<parameter key="mode" value="keep all original features"/>
<parameter key="balance for accuracy" value="1.0"/>
<parameter key="show progress dialog" value="true"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="use optimization heuristics" value="true"/>
<parameter key="maximum generations" value="30"/>
<parameter key="population size" value="10"/>
<parameter key="use multi-starts" value="true"/>
<parameter key="number of multi-starts" value="5"/>
<parameter key="generations until multi-start" value="10"/>
<parameter key="use time limit" value="true"/>
<parameter key="time limit in seconds" value="3600"/>
<parameter key="use subset for generation" value="false"/>
<parameter key="maximum function complexity" value="10"/>
<parameter key="use_plus" value="false"/>
<parameter key="use_diff" value="false"/>
<parameter key="use_mult" value="true"/>
<parameter key="use_div" value="true"/>
<parameter key="reciprocal_value" value="true"/>
<parameter key="use_square_roots" value="false"/>
<parameter key="use_exp" value="false"/>
<parameter key="use_log" value="false"/>
<parameter key="use_absolute_values" value="false"/>
<parameter key="use_sgn" value="false"/>
<parameter key="use_min" value="false"/>
<parameter key="use_max" value="false"/>
<process expanded="true">
<operator activated="true" class="concurrency:cross_validation" compatibility="9.10.001" expanded="true" height="145" name="FE Cross Validation" width="90" x="246" y="34">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="stratified sampling"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="concurrency:parallel_random_forest" compatibility="9.10.001" expanded="true" height="103" name="FE Random Forest" width="90" x="112" y="34">
<parameter key="number_of_trees" value="100"/>
<parameter key="criterion" value="gini_index"/>
<parameter key="maximal_depth" value="15"/>
<parameter key="apply_pruning" value="false"/>
<parameter key="confidence" value="0.1"/>
<parameter key="apply_prepruning" value="false"/>
<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"/>
<parameter key="random_splits" value="false"/>
<parameter key="guess_subset_ratio" value="true"/>
<parameter key="subset_ratio" value="0.2"/>
<parameter key="voting_strategy" value="confidence vote"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
</operator>
<connect from_port="training set" to_op="FE Random Forest" to_port="training set"/>
<connect from_op="FE Random Forest" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="7.1.001" expanded="true" height="82" name="FE Apply Model" origin="GENERATED_TUTORIAL" width="90" x="45" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance_binominal_classification" compatibility="9.10.001" expanded="true" height="82" name="FE Performance" width="90" x="179" y="34">
<parameter key="manually_set_positive_class" value="false"/>
<parameter key="main_criterion" value="first"/>
<parameter key="accuracy" value="false"/>
<parameter key="classification_error" value="true"/>
<parameter key="kappa" value="false"/>
<parameter key="AUC (optimistic)" value="false"/>
<parameter key="AUC" value="false"/>
<parameter key="AUC (pessimistic)" value="false"/>
<parameter key="precision" value="false"/>
<parameter key="recall" value="false"/>
<parameter key="lift" value="false"/>
<parameter key="fallout" value="false"/>
<parameter key="f_measure" value="false"/>
<parameter key="false_positive" value="false"/>
<parameter key="false_negative" value="false"/>
<parameter key="true_positive" value="false"/>
<parameter key="true_negative" value="false"/>
<parameter key="sensitivity" value="false"/>
<parameter key="specificity" value="false"/>
<parameter key="youden" value="false"/>
<parameter key="positive_predictive_value" value="false"/>
<parameter key="negative_predictive_value" value="false"/>
<parameter key="psep" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="FE Apply Model" to_port="model"/>
<connect from_port="test set" to_op="FE Apply Model" to_port="unlabelled data"/>
<connect from_op="FE Apply Model" from_port="labelled data" to_op="FE Performance" to_port="labelled data"/>
<connect from_op="FE Performance" from_port="performance" to_port="performance 1"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
<connect from_port="example set source" to_op="FE Cross Validation" to_port="example set"/>
<connect from_op="FE Cross Validation" from_port="performance 1" to_port="performance sink"/>
<portSpacing port="source_example set source" spacing="0"/>
<portSpacing port="sink_performance sink" spacing="0"/>
</process>
</operator>
<operator activated="true" class="multiply" compatibility="9.10.001" expanded="true" height="103" name="Multiply FeatureSet" width="90" x="581" y="85"/>
<operator activated="true" class="model_simulator:apply_feature_set" compatibility="9.10.001" expanded="true" height="82" name="Apply FE to TrainingData" width="90" x="715" y="34">
<parameter key="handle missings" value="true"/>
<parameter key="keep originals" value="false"/>
<parameter key="originals special role" value="true"/>
<parameter key="recreate missing attributes" value="true"/>
</operator>
<connect from_port="in 1" to_op="Multiply Preprocessed dataset" to_port="input"/>
<connect from_op="Multiply Preprocessed dataset" from_port="output 1" to_op="Apply FE to TrainingData" to_port="example set"/>
<connect from_op="Multiply Preprocessed dataset" from_port="output 2" to_op="Attribute Filtering" to_port="example set input"/>
<connect from_op="Attribute Filtering" from_port="example set output" to_op="Sample down for FE" to_port="example set input"/>
<connect from_op="Sample down for FE" from_port="example set output" to_op="FE" to_port="example set in"/>
<connect from_op="FE" from_port="feature set" to_op="Multiply FeatureSet" to_port="input"/>
<connect from_op="FE" from_port="population" to_port="out 4"/>
<connect from_op="FE" from_port="optimization log" to_port="out 2"/>
<connect from_op="Multiply FeatureSet" from_port="output 1" to_op="Apply FE to TrainingData" to_port="feature set"/>
<connect from_op="Multiply FeatureSet" from_port="output 2" to_port="out 3"/>
<connect from_op="Apply FE to TrainingData" from_port="example set" to_port="out 1"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
<portSpacing port="sink_out 3" spacing="0"/>
<portSpacing port="sink_out 4" spacing="0"/>
<portSpacing port="sink_out 5" spacing="0"/>
</process>
</operator>
<operator activated="true" class="subprocess" compatibility="9.10.001" expanded="true" height="82" name="Create Training Set" width="90" x="447" y="187">
<process expanded="true">
<operator activated="true" class="extract_macro" compatibility="9.10.001" expanded="true" height="68" name="Count CKD examples" width="90" x="112" y="34">
<parameter key="macro" value="ckdcount"/>
<parameter key="macro_type" value="statistics"/>
<parameter key="statistics" value="count"/>
<parameter key="attribute_name" value="ckd"/>
<parameter key="attribute_value" value="ckd"/>
<list key="additional_macros"/>
</operator>
<operator activated="true" class="sample" compatibility="9.10.001" expanded="true" height="82" name="Balanced Training Data" width="90" x="246" y="34">
<parameter key="sample" value="absolute"/>
<parameter key="balance_data" value="true"/>
<parameter key="sample_size" value="100"/>
<parameter key="sample_ratio" value="0.1"/>
<parameter key="sample_probability" value="0.1"/>
<list key="sample_size_per_class">
<parameter key="ckd" value="%{ckdcount}"/>
<parameter key="notckd" value="%{ckdcount}"/>
</list>
<list key="sample_ratio_per_class"/>
<list key="sample_probability_per_class"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<operator activated="false" class="sample" compatibility="9.10.001" expanded="true" height="82" name="Sample down training data" width="90" x="380" y="238">
<parameter key="sample" value="relative"/>
<parameter key="balance_data" value="false"/>
<parameter key="sample_size" value="100"/>
<parameter key="sample_ratio" value="0.5"/>
<parameter key="sample_probability" value="0.1"/>
<list key="sample_size_per_class"/>
<list key="sample_ratio_per_class"/>
<list key="sample_probability_per_class"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<operator activated="false" class="sample_stratified" compatibility="9.10.001" expanded="true" height="82" name="Sample (Stratified)" width="90" x="246" y="238">
<parameter key="sample" value="relative"/>
<parameter key="sample_size" value="100"/>
<parameter key="sample_ratio" value="0.5"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<connect from_port="in 1" to_op="Count CKD examples" to_port="example set"/>
<connect from_op="Count CKD examples" from_port="example set" to_op="Balanced Training Data" to_port="example set input"/>
<connect from_op="Balanced Training Data" from_port="example set output" to_port="out 1"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
</process>
</operator>
<connect from_port="in 1" to_op="Remove Correlated Attributes" to_port="example set input"/>
<connect from_op="Remove Correlated Attributes" from_port="example set output" to_op="Outlier elimination" to_port="in 1"/>
<connect from_op="Outlier elimination" from_port="out 1" to_port="out 1"/>
<connect from_op="Outlier elimination" from_port="out 2" to_op="Auto FE" to_port="in 1"/>
<connect from_op="Auto FE" from_port="out 1" to_op="Create Training Set" to_port="in 1"/>
<connect from_op="Auto FE" from_port="out 2" to_port="out 2"/>
<connect from_op="Auto FE" from_port="out 3" to_port="out 3"/>
<connect from_op="Auto FE" from_port="out 4" to_port="out 5"/>
<connect from_op="Create Training Set" from_port="out 1" to_port="out 4"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
<portSpacing port="sink_out 3" spacing="0"/>
<portSpacing port="sink_out 4" spacing="0"/>
<portSpacing port="sink_out 5" spacing="0"/>
<portSpacing port="sink_out 6" spacing="0"/>
</process>
</operator>
<operator activated="true" class="subprocess" compatibility="9.10.001" expanded="true" height="103" name="Test Data Preparation" width="90" x="380" y="238">
<process expanded="true">
<operator activated="true" class="model_simulator:apply_feature_set" compatibility="9.10.001" expanded="true" height="82" name="Apply FS to Scoring" width="90" x="112" y="34">
<parameter key="handle missings" value="false"/>
<parameter key="keep originals" value="false"/>
<parameter key="originals special role" value="true"/>
<parameter key="recreate missing attributes" value="false"/>
</operator>
<operator activated="true" class="extract_macro" compatibility="9.10.001" expanded="true" height="68" name="Count CKD in Scoring" width="90" x="246" y="34">
<parameter key="macro" value="ckdcount"/>
<parameter key="macro_type" value="statistics"/>
<parameter key="statistics" value="count"/>
<parameter key="attribute_name" value="ckd"/>
<parameter key="attribute_value" value="ckd"/>
<list key="additional_macros"/>
</operator>
<operator activated="true" class="sample" compatibility="9.10.001" expanded="true" height="82" name="Balanced Scoring Data" width="90" x="380" y="34">
<parameter key="sample" value="absolute"/>
<parameter key="balance_data" value="true"/>
<parameter key="sample_size" value="100"/>
<parameter key="sample_ratio" value="0.1"/>
<parameter key="sample_probability" value="0.1"/>
<list key="sample_size_per_class">
<parameter key="ckd" value="%{ckdcount}"/>
<parameter key="notckd" value="%{ckdcount}"/>
</list>
<list key="sample_ratio_per_class"/>
<list key="sample_probability_per_class"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<operator activated="false" class="sample_stratified" compatibility="9.10.001" expanded="true" height="82" name="Sample (Stratified) (2)" width="90" x="514" y="391">
<parameter key="sample" value="relative"/>
<parameter key="sample_size" value="100"/>
<parameter key="sample_ratio" value="0.5"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<operator activated="false" class="sample" compatibility="9.10.001" expanded="true" height="82" name="Sample down scoring data" width="90" x="380" y="340">
<parameter key="sample" value="relative"/>
<parameter key="balance_data" value="false"/>
<parameter key="sample_size" value="100"/>
<parameter key="sample_ratio" value="0.5"/>
<parameter key="sample_probability" value="0.1"/>
<list key="sample_size_per_class"/>
<list key="sample_ratio_per_class"/>
<list key="sample_probability_per_class"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<connect from_port="in 1" to_op="Apply FS to Scoring" to_port="example set"/>
<connect from_port="in 2" to_op="Apply FS to Scoring" to_port="feature set"/>
<connect from_op="Apply FS to Scoring" from_port="example set" to_op="Count CKD in Scoring" to_port="example set"/>
<connect from_op="Apply FS to Scoring" from_port="feature set" to_port="out 2"/>
<connect from_op="Count CKD in Scoring" from_port="example set" to_op="Balanced Scoring Data" to_port="example set input"/>
<connect from_op="Balanced Scoring Data" from_port="example set output" to_port="out 1"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="source_in 3" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
<portSpacing port="sink_out 3" spacing="0"/>
</process>
</operator>
<operator activated="true" class="subprocess" compatibility="9.10.001" expanded="true" height="145" name="Training" origin="GENERATED_AUTOMODEL" width="90" x="380" y="34">
<process expanded="true">
<operator activated="true" class="concurrency:cross_validation" compatibility="9.10.001" expanded="true" height="145" name="Cross Validation" width="90" x="246" y="34">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="stratified sampling"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="concurrency:parallel_random_forest" compatibility="9.10.001" expanded="true" height="103" name="Random Forest" width="90" x="45" y="34">
<parameter key="number_of_trees" value="100"/>
<parameter key="criterion" value="gini_index"/>
<parameter key="maximal_depth" value="15"/>
<parameter key="apply_pruning" value="false"/>
<parameter key="confidence" value="0.1"/>
<parameter key="apply_prepruning" value="false"/>
<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"/>
<parameter key="random_splits" value="false"/>
<parameter key="guess_subset_ratio" value="true"/>
<parameter key="subset_ratio" value="0.2"/>
<parameter key="voting_strategy" value="confidence vote"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
</operator>
<connect from_port="training set" to_op="Random Forest" to_port="training set"/>
<connect from_op="Random Forest" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.10.001" expanded="true" height="82" name="Apply Model" width="90" x="45" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance_binominal_classification" compatibility="9.10.001" expanded="true" height="82" name="Training Performance" width="90" x="179" y="34">
<parameter key="manually_set_positive_class" value="true"/>
<parameter key="positive_class" value="ckd"/>
<parameter key="main_criterion" value="AUC"/>
<parameter key="accuracy" value="false"/>
<parameter key="classification_error" value="false"/>
<parameter key="kappa" value="false"/>
<parameter key="AUC (optimistic)" value="false"/>
<parameter key="AUC" value="true"/>
<parameter key="AUC (pessimistic)" value="false"/>
<parameter key="precision" value="true"/>
<parameter key="recall" value="true"/>
<parameter key="lift" value="false"/>
<parameter key="fallout" value="false"/>
<parameter key="f_measure" value="true"/>
<parameter key="false_positive" value="false"/>
<parameter key="false_negative" value="false"/>
<parameter key="true_positive" value="false"/>
<parameter key="true_negative" value="false"/>
<parameter key="sensitivity" value="true"/>
<parameter key="specificity" value="true"/>
<parameter key="youden" value="false"/>
<parameter key="positive_predictive_value" value="false"/>
<parameter key="negative_predictive_value" value="false"/>
<parameter key="psep" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="Apply Model" to_port="model"/>
<connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
<connect from_op="Apply Model" from_port="labelled data" to_op="Training Performance" to_port="labelled data"/>
<connect from_op="Training Performance" from_port="performance" to_port="performance 1"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="weight_by_forest" compatibility="9.10.001" expanded="true" height="82" name="Weight by Tree Importance" width="90" x="380" y="34">
<parameter key="criterion" value="gain_ratio"/>
<parameter key="normalize_weights" value="true"/>
</operator>
<connect from_port="in 1" to_op="Cross Validation" to_port="example set"/>
<connect from_op="Cross Validation" from_port="model" to_op="Weight by Tree Importance" to_port="random forest"/>
<connect from_op="Cross Validation" from_port="example set" to_port="out 3"/>
<connect from_op="Cross Validation" from_port="performance 1" to_port="out 4"/>
<connect from_op="Weight by Tree Importance" from_port="weights" to_port="out 1"/>
<connect from_op="Weight by Tree Importance" from_port="random forest" to_port="out 2"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
<portSpacing port="sink_out 3" spacing="0"/>
<portSpacing port="sink_out 4" spacing="0"/>
<portSpacing port="sink_out 5" spacing="0"/>
</process>
</operator>
<operator activated="true" class="subprocess" compatibility="9.10.001" expanded="true" height="124" name="Scoring" width="90" x="518" y="136">
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.10.001" expanded="true" height="82" name="Apply Model On Test Data" width="90" x="246" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance_binominal_classification" compatibility="9.10.001" expanded="true" height="82" name="Scoring Performance" width="90" x="447" y="136">
<parameter key="manually_set_positive_class" value="true"/>
<parameter key="positive_class" value="ckd"/>
<parameter key="main_criterion" value="AUC"/>
<parameter key="accuracy" value="false"/>
<parameter key="classification_error" value="false"/>
<parameter key="kappa" value="false"/>
<parameter key="AUC (optimistic)" value="false"/>
<parameter key="AUC" value="true"/>
<parameter key="AUC (pessimistic)" value="false"/>
<parameter key="precision" value="true"/>
<parameter key="recall" value="true"/>
<parameter key="lift" value="true"/>
<parameter key="fallout" value="false"/>
<parameter key="f_measure" value="true"/>
<parameter key="false_positive" value="false"/>
<parameter key="false_negative" value="false"/>
<parameter key="true_positive" value="false"/>
<parameter key="true_negative" value="false"/>
<parameter key="sensitivity" value="true"/>
<parameter key="specificity" value="true"/>
<parameter key="youden" value="false"/>
<parameter key="positive_predictive_value" value="false"/>
<parameter key="negative_predictive_value" value="false"/>
<parameter key="psep" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="in 1" to_op="Apply Model On Test Data" to_port="unlabelled data"/>
<connect from_port="in 2" to_op="Apply Model On Test Data" to_port="model"/>
<connect from_op="Apply Model On Test Data" from_port="labelled data" to_op="Scoring Performance" to_port="labelled data"/>
<connect from_op="Apply Model On Test Data" from_port="model" to_port="out 2"/>
<connect from_op="Scoring Performance" from_port="performance" to_port="out 1"/>
<connect from_op="Scoring Performance" from_port="example set" to_port="out 3"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="source_in 3" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
<portSpacing port="sink_out 3" spacing="0"/>
<portSpacing port="sink_out 4" spacing="0"/>
</process>
</operator>
<connect from_op="Execute Process" from_port="result 1" to_op="Training Data Preparation" to_port="in 1"/>
<connect from_op="Execute Process" from_port="result 2" to_op="Test Data Preparation" to_port="in 1"/>
<connect from_op="Execute Process" from_port="result 3" to_port="result 11"/>
<connect from_op="Training Data Preparation" from_port="out 1" to_port="result 1"/>
<connect from_op="Training Data Preparation" from_port="out 2" to_port="result 2"/>
<connect from_op="Training Data Preparation" from_port="out 3" to_op="Test Data Preparation" to_port="in 2"/>
<connect from_op="Training Data Preparation" from_port="out 4" to_op="Training" to_port="in 1"/>
<connect from_op="Training Data Preparation" from_port="out 5" to_port="result 10"/>
<connect from_op="Test Data Preparation" from_port="out 1" to_op="Scoring" to_port="in 1"/>
<connect from_op="Test Data Preparation" from_port="out 2" to_port="result 9"/>
<connect from_op="Training" from_port="out 1" to_port="result 3"/>
<connect from_op="Training" from_port="out 2" to_op="Scoring" to_port="in 2"/>
<connect from_op="Training" from_port="out 3" to_port="result 4"/>
<connect from_op="Training" from_port="out 4" to_port="result 5"/>
<connect from_op="Scoring" from_port="out 1" to_port="result 6"/>
<connect from_op="Scoring" from_port="out 2" to_port="result 7"/>
<connect from_op="Scoring" from_port="out 3" to_port="result 8"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
<portSpacing port="sink_result 3" spacing="0"/>
<portSpacing port="sink_result 4" spacing="0"/>
<portSpacing port="sink_result 5" spacing="0"/>
<portSpacing port="sink_result 6" spacing="0"/>
<portSpacing port="sink_result 7" spacing="0"/>
<portSpacing port="sink_result 8" spacing="0"/>
<portSpacing port="sink_result 9" spacing="0"/>
<portSpacing port="sink_result 10" spacing="0"/>
<portSpacing port="sink_result 11" spacing="0"/>
<portSpacing port="sink_result 12" spacing="0"/>
</process>
</operator>
</process>