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Is this kind of flow correct?
Guru
Hi, do you think that this kind of flow is correct?
Here is the XML code:
------------------------------------------------------------------------------------------------------------
<?xml version="1.0" encoding="UTF-8"?><process version="9.2.001">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="9.2.001" expanded="true" name="Process">
<parameter key="logverbosity" value="init"/>
<parameter key="random_seed" value="2001"/>
<parameter key="send_mail" value="never"/>
<parameter key="notification_email" value=""/>
<parameter key="process_duration_for_mail" value="30"/>
<parameter key="encoding" value="SYSTEM"/>
<process expanded="true">
<operator activated="true" class="retrieve" compatibility="9.2.001" expanded="true" height="68" name="Retrieve" width="90" x="45" y="34"/>
<operator activated="true" class="set_role" compatibility="9.2.001" expanded="true" height="82" name="Set Role" width="90" x="179" y="34">
<parameter key="attribute_name" value=""/>
<parameter key="target_role" value="regular"/>
<list key="set_additional_roles"/>
</operator>
<operator activated="true" class="multiply" compatibility="9.2.001" expanded="true" height="103" name="Multiply" width="90" x="313" y="34"/>
<operator activated="true" class="filter_examples" compatibility="9.2.001" expanded="true" height="103" name="Filter Examples" 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="null.is_not_missing."/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
<operator activated="true" class="concurrency:cross_validation" compatibility="9.2.001" expanded="true" height="145" name="Cross Validation" width="90" x="581" y="34">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="automatic"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="h2o:deep_learning" compatibility="9.2.000" expanded="true" height="82" name="Deep Learning" 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_"/>
</operator>
<connect from_port="training set" to_op="Deep Learning" to_port="training set"/>
<connect from_op="Deep Learning" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.2.001" expanded="true" height="82" name="Apply Model" width="90" x="112" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance" compatibility="9.2.001" expanded="true" height="82" name="Performance" width="90" x="246" y="34">
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="Apply Model" to_port="model"/>
<connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
<connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
<connect from_op="Performance" from_port="performance" to_port="performance 1"/>
<connect from_op="Performance" from_port="example set" to_port="test set results"/>
<portSpacing port="source_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="filter_examples" compatibility="9.2.001" expanded="true" height="103" name="Filter Examples (2)" width="90" x="514" y="340">
<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="null.is_missing."/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
<operator activated="true" class="apply_model" compatibility="9.2.001" expanded="true" height="82" name="Apply Model (2)" width="90" x="782" y="136">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<connect from_op="Retrieve" from_port="output" to_op="Set Role" to_port="example set input"/>
<connect from_op="Set Role" from_port="example set output" to_op="Multiply" to_port="input"/>
<connect from_op="Multiply" from_port="output 1" to_op="Filter Examples" to_port="example set input"/>
<connect from_op="Multiply" from_port="output 2" to_op="Filter Examples (2)" to_port="example set input"/>
<connect from_op="Filter Examples" from_port="example set output" to_op="Cross Validation" to_port="example set"/>
<connect from_op="Cross Validation" from_port="model" to_op="Apply Model (2)" to_port="model"/>
<connect from_op="Filter Examples (2)" from_port="example set output" to_op="Apply Model (2)" to_port="unlabelled data"/>
<connect from_op="Apply Model (2)" from_port="labelled data" to_port="result 1"/>
<connect from_op="Apply Model (2)" from_port="model" to_port="result 2"/>
<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"/>
</process>
</operator>
</process>
Here is the XML code:
------------------------------------------------------------------------------------------------------------
<?xml version="1.0" encoding="UTF-8"?><process version="9.2.001">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="9.2.001" expanded="true" name="Process">
<parameter key="logverbosity" value="init"/>
<parameter key="random_seed" value="2001"/>
<parameter key="send_mail" value="never"/>
<parameter key="notification_email" value=""/>
<parameter key="process_duration_for_mail" value="30"/>
<parameter key="encoding" value="SYSTEM"/>
<process expanded="true">
<operator activated="true" class="retrieve" compatibility="9.2.001" expanded="true" height="68" name="Retrieve" width="90" x="45" y="34"/>
<operator activated="true" class="set_role" compatibility="9.2.001" expanded="true" height="82" name="Set Role" width="90" x="179" y="34">
<parameter key="attribute_name" value=""/>
<parameter key="target_role" value="regular"/>
<list key="set_additional_roles"/>
</operator>
<operator activated="true" class="multiply" compatibility="9.2.001" expanded="true" height="103" name="Multiply" width="90" x="313" y="34"/>
<operator activated="true" class="filter_examples" compatibility="9.2.001" expanded="true" height="103" name="Filter Examples" 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="null.is_not_missing."/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
<operator activated="true" class="concurrency:cross_validation" compatibility="9.2.001" expanded="true" height="145" name="Cross Validation" width="90" x="581" y="34">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="automatic"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="h2o:deep_learning" compatibility="9.2.000" expanded="true" height="82" name="Deep Learning" 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_"/>
</operator>
<connect from_port="training set" to_op="Deep Learning" to_port="training set"/>
<connect from_op="Deep Learning" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.2.001" expanded="true" height="82" name="Apply Model" width="90" x="112" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance" compatibility="9.2.001" expanded="true" height="82" name="Performance" width="90" x="246" y="34">
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="Apply Model" to_port="model"/>
<connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
<connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
<connect from_op="Performance" from_port="performance" to_port="performance 1"/>
<connect from_op="Performance" from_port="example set" to_port="test set results"/>
<portSpacing port="source_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="filter_examples" compatibility="9.2.001" expanded="true" height="103" name="Filter Examples (2)" width="90" x="514" y="340">
<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="null.is_missing."/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
<operator activated="true" class="apply_model" compatibility="9.2.001" expanded="true" height="82" name="Apply Model (2)" width="90" x="782" y="136">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<connect from_op="Retrieve" from_port="output" to_op="Set Role" to_port="example set input"/>
<connect from_op="Set Role" from_port="example set output" to_op="Multiply" to_port="input"/>
<connect from_op="Multiply" from_port="output 1" to_op="Filter Examples" to_port="example set input"/>
<connect from_op="Multiply" from_port="output 2" to_op="Filter Examples (2)" to_port="example set input"/>
<connect from_op="Filter Examples" from_port="example set output" to_op="Cross Validation" to_port="example set"/>
<connect from_op="Cross Validation" from_port="model" to_op="Apply Model (2)" to_port="model"/>
<connect from_op="Filter Examples (2)" from_port="example set output" to_op="Apply Model (2)" to_port="unlabelled data"/>
<connect from_op="Apply Model (2)" from_port="labelled data" to_port="result 1"/>
<connect from_op="Apply Model (2)" from_port="model" to_port="result 2"/>
<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"/>
</process>
</operator>
</process>
Tagged:
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Best Answer
-
sgenzer
Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,959 
Community Manager
yes I think you have the basic idea.
Scott
5
