predict unemployment rate using neural network

doeyiendoeyien Member Posts: 6 Contributor I
edited December 2018 in Help

Hi,here is my xml proces:..i wanna know if im doing this right.so many things required as i click run.i want to achieve the best neural network model of my data,performance of my model,the division set, the training and testing performance,when can i say that i already have the best model that i can alreay use for prediction,what is wrong with my data?how do i make the lables?i dont understand it clearly.and more if u can suggest..my target variable is unemployment rate, the rest are independent variables.Can anyone please help me...thank you very much

<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="filter_examples" compatibility="8.1.001" expanded="true" height="103" name="Filter Examples" width="90" x="179" y="136">
<parameter key="parameter_expression" value=""/>
<parameter key="condition_class" value="all"/>
<parameter key="invert_filter" value="false"/>
<list key="filters_list">
<parameter key="filters_entry_key" value="Population.is_not_missing."/>
<parameter key="filters_entry_key" value="Labor force.is_not_missing."/>
<parameter key="filters_entry_key" value="Inflation.is_not_missing."/>
<parameter key="filters_entry_key" value="GDP.is_not_missing."/>
<parameter key="filters_entry_key" value="GNI.is_not_missing."/>
<parameter key="filters_entry_key" value="GDI.is_not_missing."/>
<parameter key="filters_entry_key" value="FOREIGN TRADE.is_not_missing."/>
<parameter key="filters_entry_key" value="INDUSTRY.is_not_missing."/>
<parameter key="filters_entry_key" value="ELEM.is_not_missing."/>
<parameter key="filters_entry_key" value="SECOND.is_not_missing."/>
<parameter key="filters_entry_key" value="HIGHERED.is_not_missing."/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="normalize" compatibility="8.1.001" expanded="true" height="103" name="Normalize" width="90" x="179" y="238">
<parameter key="return_preprocessing_model" value="false"/>
<parameter key="create_view" value="false"/>
<parameter key="attribute_filter_type" value="all"/>
<parameter key="attribute" value=""/>
<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"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="set_role" compatibility="8.1.001" expanded="true" height="82" name="Set Role" width="90" x="179" y="340">
<parameter key="attribute_name" value="Unemployment"/>
<parameter key="target_role" value="label"/>
<list key="set_additional_roles">
<parameter key="Population" value="regular"/>
<parameter key="Labor force" value="regular"/>
<parameter key="Inflation" value="regular"/>
<parameter key="GDP" value="regular"/>
<parameter key="GNI" value="regular"/>
<parameter key="GDI" value="regular"/>
<parameter key="FOREIGN TRADE" value="regular"/>
<parameter key="INDUSTRY" value="regular"/>
<parameter key="ELEM" value="regular"/>
<parameter key="SECOND" value="regular"/>
<parameter key="HIGHERED" value="regular"/>
</list>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="replace_missing_values" compatibility="8.1.001" expanded="true" height="103" name="Replace Missing Values" width="90" x="313" y="238">
<parameter key="return_preprocessing_model" value="false"/>
<parameter key="create_view" value="false"/>
<parameter key="attribute_filter_type" value="all"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value=""/>
<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="false"/>
<parameter key="default" value="average"/>
<list key="columns"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="split_data" compatibility="8.1.001" expanded="true" height="103" name="Split Data" width="90" x="447" y="289">
<enumeration key="partitions">
<parameter key="ratio" value="0.9"/>
<parameter key="ratio" value="0.1"/>
</enumeration>
<parameter key="sampling_type" value="linear sampling"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="neural_net" compatibility="8.1.001" expanded="true" height="82" name="Neural Net" width="90" x="380" y="85">
<list key="hidden_layers"/>
<parameter key="training_cycles" value="500"/>
<parameter key="learning_rate" value="0.3"/>
<parameter key="momentum" value="0.2"/>
<parameter key="decay" value="false"/>
<parameter key="shuffle" value="true"/>
<parameter key="normalize" value="true"/>
<parameter key="error_epsilon" value="1.0E-5"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model" width="90" x="514" y="85">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="performance" compatibility="8.1.001" expanded="true" height="82" name="Performance" width="90" x="782" y="85">
<parameter key="use_example_weights" value="true"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model (2)" width="90" x="648" y="289">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="performance" compatibility="8.1.001" expanded="true" height="82" name="Performance (2)" width="90" x="849" y="289">
<parameter key="use_example_weights" value="true"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="retrieve" compatibility="8.1.001" expanded="true" height="68" name="Retrieve MYDATA - Copy (2)" width="90" x="313" y="493">
<parameter key="repository_entry" value="//NewLocalRepository/MYDATA - Copy"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="filter_examples" compatibility="8.1.001" expanded="true" height="103" name="Filter Examples (2)" width="90" x="447" y="493">
<parameter key="parameter_expression" value=""/>
<parameter key="condition_class" value="all"/>
<parameter key="invert_filter" value="false"/>
<list key="filters_list">
<parameter key="filters_entry_key" value="Unemployment.is_missing."/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="normalize" compatibility="8.1.001" expanded="true" height="103" name="Normalize (2)" width="90" x="581" y="493">
<parameter key="return_preprocessing_model" value="false"/>
<parameter key="create_view" value="false"/>
<parameter key="attribute_filter_type" value="all"/>
<parameter key="attribute" value=""/>
<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"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="set_role" compatibility="8.1.001" expanded="true" height="82" name="Set Role (2)" width="90" x="715" y="493">
<parameter key="attribute_name" value="Unemployment"/>
<parameter key="target_role" value="label"/>
<list key="set_additional_roles"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="replace_missing_values" compatibility="8.1.001" expanded="true" height="103" name="Replace Missing Values (2)" width="90" x="782" y="595">
<parameter key="return_preprocessing_model" value="false"/>
<parameter key="create_view" value="false"/>
<parameter key="attribute_filter_type" value="all"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value=""/>
<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="false"/>
<parameter key="default" value="average"/>
<list key="columns"/>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
<operator activated="true" class="concurrency:cross_validation" compatibility="8.1.001" expanded="true" height="145" name="Cross Validation" width="90" x="916" y="442">
<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="neural_net" compatibility="8.1.001" expanded="true" height="82" name="Neural Net (2)" width="90" x="112" y="85">
<list key="hidden_layers"/>
<parameter key="training_cycles" value="500"/>
<parameter key="learning_rate" value="0.3"/>
<parameter key="momentum" value="0.2"/>
<parameter key="decay" value="false"/>
<parameter key="shuffle" value="true"/>
<parameter key="normalize" value="true"/>
<parameter key="error_epsilon" value="1.0E-5"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
</operator>
<connect from_port="training set" to_op="Neural Net (2)" to_port="training set"/>
<connect from_op="Neural Net (2)" from_port="model" to_port="model"/>
<connect from_op="Neural Net (2)" from_port="exampleSet" to_port="through 1"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
<portSpacing port="sink_through 2" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model (3)" width="90" x="45" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance_classification" compatibility="8.1.001" expanded="true" height="82" name="Performance from Cross Validation" width="90" x="246" y="34">
<parameter key="main_criterion" value="first"/>
<parameter key="accuracy" value="true"/>
<parameter key="classification_error" value="false"/>
<parameter key="kappa" value="false"/>
<parameter key="weighted_mean_recall" value="false"/>
<parameter key="weighted_mean_precision" value="false"/>
<parameter key="spearman_rho" value="false"/>
<parameter key="kendall_tau" value="false"/>
<parameter key="absolute_error" value="false"/>
<parameter key="relative_error" value="false"/>
<parameter key="relative_error_lenient" value="false"/>
<parameter key="relative_error_strict" value="false"/>
<parameter key="normalized_absolute_error" value="false"/>
<parameter key="root_mean_squared_error" value="false"/>
<parameter key="root_relative_squared_error" value="false"/>
<parameter key="squared_error" value="false"/>
<parameter key="correlation" value="false"/>
<parameter key="squared_correlation" value="false"/>
<parameter key="cross-entropy" value="false"/>
<parameter key="margin" value="false"/>
<parameter key="soft_margin_loss" value="false"/>
<parameter key="logistic_loss" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
<list key="class_weights"/>
</operator>
<connect from_port="model" to_op="Apply Model (3)" to_port="model"/>
<connect from_port="test set" to_op="Apply Model (3)" to_port="unlabelled data"/>
<connect from_op="Apply Model (3)" from_port="labelled data" to_op="Performance from Cross Validation" to_port="labelled data"/>
<connect from_op="Performance from Cross Validation" 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="source_through 2" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
</process>

 

Answers

  • Thomas_OttThomas_Ott RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,761   Unicorn
  • doeyiendoeyien Member Posts: 6 Contributor I
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="retrieve" compatibility="8.1.001" expanded="true" height="68" name="Retrieve MYDATA - Copy" width="90" x="45" y="238">
    <parameter key="repository_entry" value="//NewLocalRepository/MYDATA - Copy"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="filter_examples" compatibility="8.1.001" expanded="true" height="103" name="Filter Examples" width="90" x="179" y="238">
    <parameter key="parameter_expression" value=""/>
    <parameter key="condition_class" value="all"/>
    <parameter key="invert_filter" value="false"/>
    <list key="filters_list">
    <parameter key="filters_entry_key" value="Population.is_not_missing."/>
    <parameter key="filters_entry_key" value="Labor force.is_not_missing."/>
    <parameter key="filters_entry_key" value="Inflation.is_not_missing."/>
    <parameter key="filters_entry_key" value="GDP.is_not_missing."/>
    <parameter key="filters_entry_key" value="GNI.is_not_missing."/>
    <parameter key="filters_entry_key" value="GDI.is_not_missing."/>
    <parameter key="filters_entry_key" value="FOREIGN TRADE.is_not_missing."/>
    <parameter key="filters_entry_key" value="INDUSTRY.is_not_missing."/>
    <parameter key="filters_entry_key" value="ELEM.is_not_missing."/>
    <parameter key="filters_entry_key" value="SECOND.is_not_missing."/>
    <parameter key="filters_entry_key" value="HIGHERED.is_not_missing."/>
    </list>
    <parameter key="filters_logic_and" value="true"/>
    <parameter key="filters_check_metadata" value="true"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="normalize" compatibility="8.1.001" expanded="true" height="103" name="Normalize" width="90" x="45" y="340">
    <parameter key="return_preprocessing_model" value="false"/>
    <parameter key="create_view" value="false"/>
    <parameter key="attribute_filter_type" value="all"/>
    <parameter key="attribute" value=""/>
    <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"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="set_role" compatibility="8.1.001" expanded="true" height="82" name="Set Role" width="90" x="179" y="340">
    <parameter key="attribute_name" value="Unemployment"/>
    <parameter key="target_role" value="label"/>
    <list key="set_additional_roles">
    <parameter key="Population" value="regular"/>
    <parameter key="Labor force" value="regular"/>
    <parameter key="Inflation" value="regular"/>
    <parameter key="GDP" value="regular"/>
    <parameter key="GNI" value="regular"/>
    <parameter key="GDI" value="regular"/>
    <parameter key="FOREIGN TRADE" value="regular"/>
    <parameter key="INDUSTRY" value="regular"/>
    <parameter key="ELEM" value="regular"/>
    <parameter key="SECOND" value="regular"/>
    <parameter key="HIGHERED" value="regular"/>
    </list>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="replace_missing_values" compatibility="8.1.001" expanded="true" height="103" name="Replace Missing Values" width="90" x="313" y="340">
    <parameter key="return_preprocessing_model" value="false"/>
    <parameter key="create_view" value="false"/>
    <parameter key="attribute_filter_type" value="all"/>
    <parameter key="attribute" value=""/>
    <parameter key="attributes" value=""/>
    <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="false"/>
    <parameter key="default" value="average"/>
    <list key="columns"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="split_data" compatibility="8.1.001" expanded="true" height="103" name="Split Data" width="90" x="447" y="289">
    <enumeration key="partitions">
    <parameter key="ratio" value="0.9"/>
    <parameter key="ratio" value="0.1"/>
    </enumeration>
    <parameter key="sampling_type" value="linear sampling"/>
    <parameter key="use_local_random_seed" value="false"/>
    <parameter key="local_random_seed" value="1992"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="neural_net" compatibility="8.1.001" expanded="true" height="82" name="Neural Net" width="90" x="380" y="187">
    <list key="hidden_layers"/>
    <parameter key="training_cycles" value="500"/>
    <parameter key="learning_rate" value="0.3"/>
    <parameter key="momentum" value="0.2"/>
    <parameter key="decay" value="false"/>
    <parameter key="shuffle" value="true"/>
    <parameter key="normalize" value="true"/>
    <parameter key="error_epsilon" value="1.0E-5"/>
    <parameter key="use_local_random_seed" value="false"/>
    <parameter key="local_random_seed" value="1992"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model" width="90" x="514" y="85">
    <list key="application_parameters"/>
    <parameter key="create_view" value="false"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model (2)" width="90" x="648" y="289">
    <list key="application_parameters"/>
    <parameter key="create_view" value="false"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="performance" compatibility="8.1.001" expanded="true" height="82" name="Performance (2)" width="90" x="849" y="289">
    <parameter key="use_example_weights" value="true"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="performance" compatibility="8.1.001" expanded="true" height="82" name="Performance" width="90" x="782" y="85">
    <parameter key="use_example_weights" value="true"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="retrieve" compatibility="8.1.001" expanded="true" height="68" name="Retrieve MYDATA - Copy (2)" width="90" x="313" y="493">
    <parameter key="repository_entry" value="//NewLocalRepository/MYDATA - Copy"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="filter_examples" compatibility="8.1.001" expanded="true" height="103" name="Filter Examples (2)" width="90" x="447" y="493">
    <parameter key="parameter_expression" value=""/>
    <parameter key="condition_class" value="all"/>
    <parameter key="invert_filter" value="false"/>
    <list key="filters_list">
    <parameter key="filters_entry_key" value="Unemployment.is_missing."/>
    </list>
    <parameter key="filters_logic_and" value="true"/>
    <parameter key="filters_check_metadata" value="true"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="normalize" compatibility="8.1.001" expanded="true" height="103" name="Normalize (2)" width="90" x="581" y="493">
    <parameter key="return_preprocessing_model" value="false"/>
    <parameter key="create_view" value="false"/>
    <parameter key="attribute_filter_type" value="all"/>
    <parameter key="attribute" value=""/>
    <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"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="set_role" compatibility="8.1.001" expanded="true" height="82" name="Set Role (2)" width="90" x="715" y="493">
    <parameter key="attribute_name" value="Unemployment"/>
    <parameter key="target_role" value="label"/>
    <list key="set_additional_roles"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="replace_missing_values" compatibility="8.1.001" expanded="true" height="103" name="Replace Missing Values (2)" width="90" x="782" y="595">
    <parameter key="return_preprocessing_model" value="false"/>
    <parameter key="create_view" value="false"/>
    <parameter key="attribute_filter_type" value="all"/>
    <parameter key="attribute" value=""/>
    <parameter key="attributes" value=""/>
    <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="false"/>
    <parameter key="default" value="average"/>
    <list key="columns"/>
    </operator>
    </process>
    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <operator activated="true" class="concurrency:cross_validation" compatibility="8.1.001" expanded="true" height="145" name="Cross Validation" width="90" x="916" y="442">
    <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="neural_net" compatibility="8.1.001" expanded="true" height="82" name="Neural Net (2)" width="90" x="112" y="85">
    <list key="hidden_layers"/>
    <parameter key="training_cycles" value="500"/>
    <parameter key="learning_rate" value="0.3"/>
    <parameter key="momentum" value="0.2"/>
    <parameter key="decay" value="false"/>
    <parameter key="shuffle" value="true"/>
    <parameter key="normalize" value="true"/>
    <parameter key="error_epsilon" value="1.0E-5"/>
    <parameter key="use_local_random_seed" value="false"/>
    <parameter key="local_random_seed" value="1992"/>
    </operator>
    <connect from_port="training set" to_op="Neural Net (2)" to_port="training set"/>
    <connect from_op="Neural Net (2)" from_port="model" to_port="model"/>
    <connect from_op="Neural Net (2)" from_port="exampleSet" to_port="through 1"/>
    <portSpacing port="source_training set" spacing="0"/>
    <portSpacing port="sink_model" spacing="0"/>
    <portSpacing port="sink_through 1" spacing="0"/>
    <portSpacing port="sink_through 2" spacing="0"/>
    </process>
    <process expanded="true">
    <operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model (3)" width="90" x="45" y="34">
    <list key="application_parameters"/>
    <parameter key="create_view" value="false"/>
    </operator>
    <operator activated="true" class="performance_classification" compatibility="8.1.001" expanded="true" height="82" name="Performance from Cross Validation" width="90" x="246" y="34">
    <parameter key="main_criterion" value="first"/>
    <parameter key="accuracy" value="true"/>
    <parameter key="classification_error" value="false"/>
    <parameter key="kappa" value="false"/>
    <parameter key="weighted_mean_recall" value="false"/>
    <parameter key="weighted_mean_precision" value="false"/>
    <parameter key="spearman_rho" value="false"/>
    <parameter key="kendall_tau" value="false"/>
    <parameter key="absolute_error" value="false"/>
    <parameter key="relative_error" value="false"/>
    <parameter key="relative_error_lenient" value="false"/>
    <parameter key="relative_error_strict" value="false"/>
    <parameter key="normalized_absolute_error" value="false"/>
    <parameter key="root_mean_squared_error" value="false"/>
    <parameter key="root_relative_squared_error" value="false"/>
    <parameter key="squared_error" value="false"/>
    <parameter key="correlation" value="false"/>
    <parameter key="squared_correlation" value="false"/>
    <parameter key="cross-entropy" value="false"/>
    <parameter key="margin" value="false"/>
    <parameter key="soft_margin_loss" value="false"/>
    <parameter key="logistic_loss" value="false"/>
    <parameter key="skip_undefined_labels" value="true"/>
    <parameter key="use_example_weights" value="true"/>
    <list key="class_weights"/>
    </operator>
    <connect from_port="model" to_op="Apply Model (3)" to_port="model"/>
    <connect from_port="test set" to_op="Apply Model (3)" to_port="unlabelled data"/>
    <connect from_op="Apply Model (3)" from_port="labelled data" to_op="Performance from Cross Validation" to_port="labelled data"/>
    <connect from_op="Performance from Cross Validation" 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="source_through 2" spacing="0"/>
    <portSpacing port="sink_test set results" spacing="0"/>
    <portSpacing port="sink_performance 1" spacing="0"/>
    <portSpacing port="sink_performance 2" spacing="0"/>
    </process>
    </operator>
    </process>

    i hope this one is already ok..sorry i was ble to click 'accept as solution" earlier...

    thanks again...

  • doeyiendoeyien Member Posts: 6 Contributor I

    i'm sorry if i was able to click "accept solution" earlier,...i was trying to edit my post,..still my problems were mentioned at my post,...this is my xml process:,..i hope this one will work.

     

     

    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.001">
    <context>
    <input/>
    <output/>
    <macros/>
    </context>
    <operator activated="true" class="process" compatibility="8.1.001" expanded="true" name="Process">
    <process expanded="true">
    <operator activated="true" class="retrieve" compatibility="8.1.001" expanded="true" height="68" name="Retrieve MYDATA - Copy" width="90" x="45" y="238">
    <parameter key="repository_entry" value="//NewLocalRepository/MYDATA - Copy"/>
    </operator>
    <operator activated="true" class="filter_examples" compatibility="8.1.001" expanded="true" height="103" name="Filter Examples" width="90" x="179" y="238">
    <parameter key="condition_class" value="all"/>
    <list key="filters_list">
    <parameter key="filters_entry_key" value="Population.is_not_missing."/>
    <parameter key="filters_entry_key" value="Labor force.is_not_missing."/>
    <parameter key="filters_entry_key" value="Inflation.is_not_missing."/>
    <parameter key="filters_entry_key" value="GDP.is_not_missing."/>
    <parameter key="filters_entry_key" value="GNI.is_not_missing."/>
    <parameter key="filters_entry_key" value="GDI.is_not_missing."/>
    <parameter key="filters_entry_key" value="FOREIGN TRADE.is_not_missing."/>
    <parameter key="filters_entry_key" value="INDUSTRY.is_not_missing."/>
    <parameter key="filters_entry_key" value="ELEM.is_not_missing."/>
    <parameter key="filters_entry_key" value="SECOND.is_not_missing."/>
    <parameter key="filters_entry_key" value="HIGHERED.is_not_missing."/>
    </list>
    </operator>
    <operator activated="true" class="normalize" compatibility="8.1.001" expanded="true" height="103" name="Normalize" width="90" x="45" y="340"/>
    <operator activated="true" class="set_role" compatibility="8.1.001" expanded="true" height="82" name="Set Role" width="90" x="179" y="340">
    <parameter key="attribute_name" value="Unemployment"/>
    <parameter key="target_role" value="label"/>
    <list key="set_additional_roles">
    <parameter key="Population" value="regular"/>
    <parameter key="Labor force" value="regular"/>
    <parameter key="Inflation" value="regular"/>
    <parameter key="GDP" value="regular"/>
    <parameter key="GNI" value="regular"/>
    <parameter key="GDI" value="regular"/>
    <parameter key="FOREIGN TRADE" value="regular"/>
    <parameter key="INDUSTRY" value="regular"/>
    <parameter key="ELEM" value="regular"/>
    <parameter key="SECOND" value="regular"/>
    <parameter key="HIGHERED" value="regular"/>
    </list>
    </operator>
    <operator activated="true" class="replace_missing_values" compatibility="8.1.001" expanded="true" height="103" name="Replace Missing Values" width="90" x="313" y="340">
    <list key="columns"/>
    </operator>
    <operator activated="true" class="split_data" compatibility="8.1.001" expanded="true" height="103" name="Split Data" width="90" x="447" y="289">
    <enumeration key="partitions">
    <parameter key="ratio" value="0.9"/>
    <parameter key="ratio" value="0.1"/>
    </enumeration>
    <parameter key="sampling_type" value="linear sampling"/>
    </operator>
    <operator activated="true" class="neural_net" compatibility="8.1.001" expanded="true" height="82" name="Neural Net" width="90" x="380" y="187">
    <list key="hidden_layers"/>
    </operator>
    <operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model" width="90" x="514" y="85">
    <list key="application_parameters"/>
    </operator>
    <operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model (2)" width="90" x="648" y="289">
    <list key="application_parameters"/>
    </operator>
    <operator activated="true" class="performance" compatibility="8.1.001" expanded="true" height="82" name="Performance (2)" width="90" x="849" y="289"/>
    <operator activated="true" class="performance" compatibility="8.1.001" expanded="true" height="82" name="Performance" width="90" x="782" y="85"/>
    <operator activated="true" class="retrieve" compatibility="8.1.001" expanded="true" height="68" name="Retrieve MYDATA - Copy (2)" width="90" x="313" y="493">
    <parameter key="repository_entry" value="//NewLocalRepository/MYDATA - Copy"/>
    </operator>
    <operator activated="true" class="filter_examples" compatibility="8.1.001" expanded="true" height="103" name="Filter Examples (2)" width="90" x="447" y="493">
    <parameter key="condition_class" value="all"/>
    <list key="filters_list">
    <parameter key="filters_entry_key" value="Unemployment.is_missing."/>
    </list>
    </operator>
    <operator activated="true" class="normalize" compatibility="8.1.001" expanded="true" height="103" name="Normalize (2)" width="90" x="581" y="493"/>
    <operator activated="true" class="set_role" compatibility="8.1.001" expanded="true" height="82" name="Set Role (2)" width="90" x="715" y="493">
    <parameter key="attribute_name" value="Unemployment"/>
    <parameter key="target_role" value="label"/>
    <list key="set_additional_roles"/>
    </operator>
    <operator activated="true" class="replace_missing_values" compatibility="8.1.001" expanded="true" height="103" name="Replace Missing Values (2)" width="90" x="782" y="595">
    <list key="columns"/>
    </operator>
    <operator activated="true" class="concurrency:cross_validation" compatibility="8.1.001" expanded="true" height="145" name="Cross Validation" width="90" x="916" y="442">
    <process expanded="true">
    <operator activated="true" class="neural_net" compatibility="8.1.001" expanded="true" height="82" name="Neural Net (2)" width="90" x="112" y="85">
    <list key="hidden_layers"/>
    </operator>
    <connect from_port="training set" to_op="Neural Net (2)" to_port="training set"/>
    <connect from_op="Neural Net (2)" from_port="model" to_port="model"/>
    <connect from_op="Neural Net (2)" from_port="exampleSet" to_port="through 1"/>
    <portSpacing port="source_training set" spacing="0"/>
    <portSpacing port="sink_model" spacing="0"/>
    <portSpacing port="sink_through 1" spacing="0"/>
    <portSpacing port="sink_through 2" spacing="0"/>
    </process>
    <process expanded="true">
    <operator activated="true" class="apply_model" compatibility="8.1.001" expanded="true" height="82" name="Apply Model (3)" width="90" x="45" y="34">
    <list key="application_parameters"/>
    </operator>
    <operator activated="true" class="performance_classification" compatibility="8.1.001" expanded="true" height="82" name="Performance from Cross Validation" width="90" x="246" y="34">
    <list key="class_weights"/>
    </operator>
    <connect from_port="model" to_op="Apply Model (3)" to_port="model"/>
    <connect from_port="test set" to_op="Apply Model (3)" to_port="unlabelled data"/>
    <connect from_op="Apply Model (3)" from_port="labelled data" to_op="Performance from Cross Validation" to_port="labelled data"/>
    <connect from_op="Performance from Cross Validation" 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="source_through 2" spacing="0"/>
    <portSpacing port="sink_test set results" spacing="0"/>
    <portSpacing port="sink_performance 1" spacing="0"/>
    <portSpacing port="sink_performance 2" spacing="0"/>
    </process>
    </operator>
    <connect from_op="Retrieve MYDATA - Copy" from_port="output" to_op="Filter Examples" to_port="example set input"/>
    <connect from_op="Filter Examples" from_port="example set output" to_op="Normalize" to_port="example set input"/>
    <connect from_op="Normalize" from_port="example set output" to_op="Set Role" to_port="example set input"/>
    <connect from_op="Set Role" from_port="example set output" to_op="Replace Missing Values" to_port="example set input"/>
    <connect from_op="Replace Missing Values" from_port="example set output" to_op="Split Data" to_port="example set"/>
    <connect from_op="Split Data" from_port="partition 1" to_op="Neural Net" 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="Neural Net" from_port="model" to_op="Apply Model" to_port="model"/>
    <connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
    <connect from_op="Apply Model" from_port="model" to_op="Apply Model (2)" to_port="model"/>
    <connect from_op="Apply Model (2)" from_port="labelled data" to_op="Performance (2)" to_port="labelled data"/>
    <connect from_op="Performance (2)" from_port="performance" to_port="result 2"/>
    <connect from_op="Performance" from_port="performance" to_port="result 1"/>
    <connect from_op="Retrieve MYDATA - Copy (2)" from_port="output" to_op="Filter Examples (2)" to_port="example set input"/>
    <connect from_op="Filter Examples (2)" from_port="example set output" to_op="Normalize (2)" to_port="example set input"/>
    <connect from_op="Normalize (2)" from_port="example set output" to_op="Set Role (2)" to_port="example set input"/>
    <connect from_op="Set Role (2)" from_port="example set output" to_op="Replace Missing Values (2)" to_port="example set input"/>
    <connect from_op="Replace Missing Values (2)" from_port="example set output" to_op="Cross Validation" to_port="example set"/>
    <connect from_op="Cross Validation" from_port="model" to_port="result 3"/>
    <portSpacing port="source_input 1" spacing="0"/>
    <portSpacing port="sink_result 1" spacing="0"/>
    <portSpacing port="sink_result 2" spacing="0"/>
    <portSpacing port="sink_result 3" spacing="0"/>
    <portSpacing port="sink_result 4" spacing="0"/>
    <description align="center" color="yellow" colored="false" height="135" resized="true" width="387" x="601" y="253">This is the test data</description>
    <description align="center" color="yellow" colored="false" height="135" resized="true" width="620" x="368" y="52">This is the training data</description>
    </process>
    </operator>
    </process>

    Can anyone please help me....

  • JEdwardJEdward RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 563   Unicorn

    Okay, great. Your XML now loads, but it seems it's a bit unclear what your goal is for the data.

     

    A couple of points, the data you provided looks a little like a time series, is that correct?  Or is it to produce a prediction of the unemployment rate

     

    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.000">
    <context>
    <input/>
    <output/>
    <macros/>
    </context>
    <operator activated="true" class="process" compatibility="8.1.000" expanded="true" name="Process">
    <process expanded="true">
    <operator activated="true" class="operator_toolbox:create_exampleset_from_doc" compatibility="0.9.000" expanded="true" height="68" name="MyData" width="90" x="45" y="34">
    <parameter key="Column Separator" value="&#9;"/>
    <parameter key="Input Csv" value="Population&#9;Labor force &#9;Inflation &#9;GDP&#9;GNI&#9;GDI&#9;FOREIGN TRADE&#9;INDUSTRY&#9;ELEM&#9;SECOND&#9;HIGHERED&#9;Unemployment&#10;99,880,300&#9;64.6&#9;4.1&#9;12,645,271&#9;15,306,201&#9;20.9&#9;127,499.60&#9;184.8&#9;80.63&#9;80.58&#9;585,288&#9;6.6&#10;98,196,500&#9;63.9&#9;3&#9;11,538,410&#9;14,018,990&#9;19.7&#9;119,108.43&#9;174&#9;74.23&#9;78.2&#9;564,769&#9;7.1&#10;96,510,900&#9;64.2&#9;3.2&#9;10,561,089&#9;12,727,240&#9;18.5&#9;114,228.18&#9;165.1&#9;73.76&#9;78.83&#9;522,570&#9;7.0&#10;94,823,800&#9;64.1&#9;4.6&#9;9,708,332&#9;11,629,304&#9;20.5&#9;108,800.76&#9;154.2&#9;74.23&#9;79.43&#9;496,949&#9;7.0&#10;92,337,852&#9;64.0&#9;3.8&#9;9,003,480&#9;10,852,432&#9;20.5&#9;106,430.43&#9;151&#9;74.38&#9;78.44&#9;481,862&#9;7.3&#10;92,226,600&#9;64.0&#9;4.2&#9;8,026,143&#9;9,738,233&#9;16.6&#9;81,527.33&#9;129.2&#9;75.39&#9;79.73&#9;469,654&#9;7.5&#10;90,457,200&#9;63.6&#9;8.3&#9;7,720,903&#9;9,063,118&#9;19.3&#9;105,823.60&#9;148.7&#9;75.26&#9;79.91&#9;444,815&#9;7.4&#10;88,548,366&#9;64.0&#9;2.9&#9;6,892,721&#9;8,068,166&#9;17.3&#9;105,979.47&#9;142.4&#9;73.43&#9;77.33&#9;444,427&#9;7.3&#10;86,972,000&#9;64.2&#9;6.2&#9;6,271,157&#9;7,386,085&#9;18&#9;99,183.80&#9;256.9&#9;70.02&#9;67.32&#9;421,444&#9;8.0&#10;85,261,000&#9;64.7&#9;7.6&#9;5,677,750&#9;6,731,531&#9;21.6&#9;88,672.87&#9;250.6&#9;71.32&#9;78.09&#9;409,628&#9;7.8&#10;83,558,700&#9;67.5&#9;6&#9;5,120,435&#9;6,033,825&#9;21.6&#9;83,719.73&#9;221.8&#9;71.84&#9;77.71&#9;386,920&#9;11.8&#10;81,877,700&#9;66.7&#9;3.5&#9;4,548,102&#9;5,371,105&#9;23&#9;76,701.72&#9;204&#9;72.44&#9;76.99&#9;405,716&#9;11.4&#10;80,217,200&#9;67.4&#9;3&#9;4,198,345&#9;4,979,157&#9;24.5&#9;74,444.67&#9;188.8&#9;67.13&#9;73.16&#9;383,839&#9;11.4&#10;78,568,000&#9;67.1&#9;6.8&#9;3,888,801&#9;4,593,961&#9;22.1&#9;65,207.36&#9;193.4&#9;67.18&#9;73.05&#9;363,640&#9;11.1&#10;76,506,928&#9;64.3&#9;4.3&#9;3,580,714&#9;4,196,876&#9;29.1&#9;72,569.12&#9;631.4&#9;69.29&#9;71.02&#9;350,807&#9;10.1&#10;76,782,548&#9;65.8&#9;6.7&#9;3,244,197&#9;3,691,995&#9;18.8&#9;65,779.35&#9;500.1&#9;69.75&#9;71.25&#9;334,564&#9;9.4&#10;75,154,743&#9;66.0&#9;9.8&#9;2,952,762&#9;3,378,003&#9;20.3&#9;59,156.24&#9;467.5&#9;68.68&#9;71.4&#9;307,027&#9;9.6&#10;73,526,941&#9;65.5&#9;5.9&#9;2,426,743&#9;2,528,321&#9;23.8&#9;61,161.52&#9;471.2&#9;67.96&#9;73.45&#9;335,257&#9;7.9&#10;71,899,136&#9;65.8&#9;9&#9;2,171,922&#9;2,261,339&#9;23.1&#9;52,969.48&#9;437.9&#9;67.16&#9;72.97&#9;328,120&#9;7.4&#10;68,616,536&#9;65.6&#9;8&#9;1,905,951&#9;1,958,555&#9;22.5&#9;43,984.82&#9;400.9&#9;66.5&#9;75.59&#9;312,667&#9;8.4&#10;66,624,247&#9;64.4&#9;8.3&#9;1,692,932&#9;1,736,382&#9;23.5&#9;34,815.47&#9;342.4&#9;67.5&#9;75.86&#9;319,372&#9;8.4&#10;66,981,614&#9;64.7&#9;7&#9;1,474,457&#9;1,509,507&#9;23.6&#9;28,972.20&#9;301&#9;68.38&#9;71.98&#9;355,469&#9;8.9&#10;65,338,989&#9;65.0&#9;8.6&#9;1,351,559&#9;1,374,838&#9;20.8&#9;24,343.24&#9;256&#9;68.65&#9;73.43&#9;306,719&#9;8.6&#10;63,691,858&#9;64.5&#9;18.5&#9;1,248,011&#9;1,254,562&#9;19.9&#9;20,890.87&#9;241&#9;69.74&#9;76.41&#9;310,554&#9;9.0&#10;&#10;"/>
    </operator>
    <operator activated="true" class="parse_numbers" compatibility="8.1.000" expanded="true" height="82" name="Parse Numbers" width="90" x="179" y="34">
    <parameter key="grouped_digits" value="true"/>
    </operator>
    <operator activated="true" class="set_role" compatibility="8.1.000" expanded="true" height="82" name="Set Role" width="90" x="112" y="136">
    <parameter key="attribute_name" value="Unemployment"/>
    <parameter key="target_role" value="label"/>
    <list key="set_additional_roles"/>
    </operator>
    <operator activated="true" class="split_data" compatibility="8.1.000" expanded="true" height="103" name="Split Data" width="90" x="246" y="187">
    <enumeration key="partitions">
    <parameter key="ratio" value="0.9"/>
    <parameter key="ratio" value="0.1"/>
    </enumeration>
    <parameter key="sampling_type" value="linear sampling"/>
    </operator>
    <operator activated="true" class="concurrency:cross_validation" compatibility="8.1.000" expanded="true" height="145" name="Cross Validation" width="90" x="447" y="85">
    <process expanded="true">
    <operator activated="true" class="normalize" compatibility="8.1.000" expanded="true" height="103" name="Normalize" width="90" x="45" y="34"/>
    <operator activated="true" class="replace_missing_values" compatibility="8.1.000" expanded="true" height="103" name="Replace Missing Values" width="90" x="179" y="85">
    <list key="columns"/>
    </operator>
    <operator activated="true" class="neural_net" compatibility="8.1.000" expanded="true" height="82" name="Neural Net" width="90" x="313" y="136">
    <list key="hidden_layers"/>
    </operator>
    <operator activated="true" class="group_models" compatibility="8.1.000" expanded="true" height="124" name="Group Models" width="90" x="447" y="34"/>
    <connect from_port="training set" to_op="Normalize" to_port="example set input"/>
    <connect from_op="Normalize" from_port="example set output" to_op="Replace Missing Values" to_port="example set input"/>
    <connect from_op="Normalize" from_port="preprocessing model" to_op="Group Models" to_port="models in 1"/>
    <connect from_op="Replace Missing Values" from_port="example set output" to_op="Neural Net" to_port="training set"/>
    <connect from_op="Replace Missing Values" from_port="preprocessing model" to_op="Group Models" to_port="models in 2"/>
    <connect from_op="Neural Net" from_port="model" to_op="Group Models" to_port="models in 3"/>
    <connect from_op="Group Models" from_port="model out" to_port="model"/>
    <portSpacing port="source_training set" spacing="0"/>
    <portSpacing port="sink_model" spacing="0"/>
    <portSpacing port="sink_through 1" spacing="0"/>
    <description align="center" color="yellow" colored="false" height="85" resized="true" width="518" x="15" y="278">Best practice is to perform preprocessing such as normalize &amp;amp; replace missing values within the model training and reapply the exact same step in model testing. &lt;br/&gt;To do this we use the Group Models operator to save the steps in order.</description>
    </process>
    <process expanded="true">
    <operator activated="true" class="apply_model" compatibility="8.1.000" expanded="true" height="82" name="Apply Model" width="90" x="45" y="34">
    <list key="application_parameters"/>
    </operator>
    <operator activated="true" class="performance_regression" compatibility="8.1.000" expanded="true" height="82" name="Performance Training" width="90" x="179" y="34"/>
    <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 Training" to_port="labelled data"/>
    <connect from_op="Performance Training" 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="apply_model" compatibility="8.1.000" expanded="true" height="82" name="Apply Model (2)" width="90" x="648" y="289">
    <list key="application_parameters"/>
    </operator>
    <operator activated="true" class="performance_regression" compatibility="8.1.000" expanded="true" height="82" name="Performance Testing" width="90" x="849" y="289"/>
    <connect from_op="MyData" from_port="output" to_op="Parse Numbers" to_port="example set input"/>
    <connect from_op="Parse Numbers" from_port="example set output" to_op="Set Role" to_port="example set input"/>
    <connect from_op="Set Role" from_port="example set output" to_op="Split Data" to_port="example set"/>
    <connect from_op="Split Data" from_port="partition 1" to_op="Cross Validation" to_port="example set"/>
    <connect from_op="Split Data" from_port="partition 2" to_op="Apply Model (2)" to_port="unlabelled data"/>
    <connect from_op="Cross Validation" from_port="model" to_op="Apply Model (2)" to_port="model"/>
    <connect from_op="Cross Validation" from_port="performance 1" to_port="result 1"/>
    <connect from_op="Apply Model (2)" from_port="labelled data" to_op="Performance Testing" to_port="labelled data"/>
    <connect from_op="Apply Model (2)" from_port="model" to_port="result 3"/>
    <connect from_op="Performance Testing" from_port="performance" to_port="result 2"/>
    <connect from_op="Performance Testing" from_port="example set" to_port="result 4"/>
    <portSpacing port="source_input 1" spacing="0"/>
    <portSpacing port="sink_result 1" spacing="105"/>
    <portSpacing port="sink_result 2" spacing="84"/>
    <portSpacing port="sink_result 3" spacing="42"/>
    <portSpacing port="sink_result 4" spacing="105"/>
    <portSpacing port="sink_result 5" spacing="63"/>
    <description align="center" color="yellow" colored="false" height="163" resized="true" width="622" x="366" y="253">This is the test data</description>
    <description align="center" color="yellow" colored="false" height="186" resized="true" width="617" x="368" y="52">This is the training data</description>
    <description align="center" color="purple" colored="true" height="129" resized="true" width="508" x="12" y="386">Please note, the dataset is pretty small and it's unclear currently if the data is a timeseries or just numbers.&lt;br&gt;Try changing the neural network operator to something else to see if the performance improves. Biggest recommendation is increasing the size of the dataset. You have only two records for testing in this setup.</description>
    </process>
    </operator>
    </process>
    sgenzerdoeyien
  • doeyiendoeyien Member Posts: 6 Contributor I

    Hi jEdward

    thanks for paying attention on my post

    Yes its a timeseries,..at the same time i have to make also predictions of unemployment rates ,..correct me if im wrong with my understading,.

    Can you please suggest to me on what am i going to do with this?what about my process?am i doing the right thing?

    its my first time using RM,

    thanks in advance

     

    regards,

    yien

     

     

    regard

    sgenzer
  • doeyiendoeyien Member Posts: 6 Contributor I

    heres another question,..am i going to include the variable YEAR in my data set?,..my data are from 1991-2014

  • JEdwardJEdward RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 563   Unicorn

    @doeyien

    Download the Time Series extension from the marketplace.  It adds a number of sample processes using similar datasets to yours.

    Have an explore of them to get a full understanding. 

    sgenzer
  • doeyiendoeyien Member Posts: 6 Contributor I

    thanks for ur suggestion JEdward

     

    I'll read and try the samples given

     

    More power!

    sgenzer
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