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predict unemployment rate using neural network
Learner IIIHi,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>
Tagged:
0
Answers
@doeyien your XML is corrupt. Please read this KB article on how to share it correctly. https://community.rapidminer.com/t5/RapidMiner-Studio-Knowledge-Base/How-can-I-share-processes-without-RapidMiner-Server/ta-p/37047
i hope this one is already ok..sorry i was ble to click 'accept as solution" earlier...
thanks again...
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.
Can anyone please help me....
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
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
heres another question,..am i going to include the variable YEAR in my data set?,..my data are from 1991-2014
@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.
thanks for ur suggestion JEdward
I'll read and try the samples given
More power!