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"Association Rules and root mean squared error"
flaviorrrl
Member Posts: 9 
Contributor II
Hi,
I would like to know how to calculate the root mean squared error in the associaton rule. I calculated the root mean squared error in classification algorithms (apply model + performance-classification), but I wonder if you could help me to calculate root mean squared in the association rules and clusteting. I need compare all models.
Sorry my message be extensive.
Can you help me with this issue please? How to calculate root mean squared error in association rules?
Regards,
flaviorrl
I would like to know how to calculate the root mean squared error in the associaton rule. I calculated the root mean squared error in classification algorithms (apply model + performance-classification), but I wonder if you could help me to calculate root mean squared in the association rules and clusteting. I need compare all models.
XML Classification Calculation:XML association rules???
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.3.015">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.3.015" expanded="true" name="Process">
<process expanded="true">
<operator activated="true" class="retrieve" compatibility="5.3.015" expanded="true" height="60" name="Retrieve Data2001" width="90" x="45" y="255">
<parameter key="repository_entry" value="Data/Data2001"/>
</operator>
<operator activated="true" class="replace_missing_values" compatibility="5.3.015" expanded="true" height="94" name="Replace Missing Values" width="90" x="179" y="75">
<list key="columns"/>
</operator>
<operator activated="true" class="optimize_selection_evolutionary" compatibility="5.3.015" expanded="true" height="94" name="Optimize Selection (Evolutionary)" width="90" x="447" y="75">
<parameter key="restrict_maximum" value="true"/>
<parameter key="min_number_of_attributes" value="4"/>
<parameter key="max_number_of_attributes" value="30"/>
<parameter key="population_size" value="10"/>
<parameter key="maximum_number_of_generations" value="25"/>
<process expanded="true">
<operator activated="true" class="split_validation" compatibility="5.3.015" expanded="true" height="112" name="Validation" width="90" x="313" y="120">
<process expanded="true">
<operator activated="true" class="naive_bayes" compatibility="5.3.015" expanded="true" height="76" name="Naive Bayes (2)" width="90" x="179" y="165"/>
<connect from_port="training" to_op="Naive Bayes (2)" to_port="training set"/>
<connect from_op="Naive Bayes (2)" from_port="model" to_port="model"/>
<portSpacing port="source_training" 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="5.3.015" expanded="true" height="76" name="Apply Model" width="90" x="112" y="120">
<list key="application_parameters"/>
</operator>
<operator activated="true" class="performance_classification" compatibility="5.3.015" expanded="true" height="76" name="Performance (2)" width="90" x="313" y="165">
<parameter key="root_mean_squared_error" value="true"/>
<parameter key="correlation" value="true"/>
<list key="class_weights"/>
</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 (2)" to_port="labelled data"/>
<connect from_op="Performance (2)" from_port="performance" to_port="averagable 1"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_averagable 1" spacing="0"/>
<portSpacing port="sink_averagable 2" spacing="0"/>
</process>
</operator>
<connect from_port="example set" to_op="Validation" to_port="training"/>
<connect from_op="Validation" from_port="averagable 1" to_port="performance"/>
<portSpacing port="source_example set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_performance" spacing="0"/>
</process>
</operator>
<operator activated="true" class="loop" compatibility="5.3.015" expanded="true" height="112" name="Loop" width="90" x="715" y="165">
<process expanded="true">
<operator activated="true" class="split_validation" compatibility="5.3.015" expanded="true" height="112" name="Validation (3)" width="90" x="246" y="165">
<process expanded="true">
<operator activated="true" class="select_subprocess" compatibility="5.3.015" expanded="true" height="94" name="Select Subprocess" width="90" x="179" y="75">
<parameter key="select_which" value="3"/>
<process expanded="true">
<operator activated="true" class="decision_tree" compatibility="5.3.015" expanded="true" height="76" name="Decision Tree" width="90" x="112" y="165"/>
<connect from_port="input 1" to_op="Decision Tree" to_port="training set"/>
<connect from_op="Decision Tree" from_port="model" to_port="output 1"/>
<connect from_op="Decision Tree" from_port="exampleSet" to_port="output 2"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="source_input 3" spacing="0"/>
<portSpacing port="sink_output 1" spacing="0"/>
<portSpacing port="sink_output 2" spacing="0"/>
<portSpacing port="sink_output 3" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="naive_bayes" compatibility="5.3.015" expanded="true" height="76" name="Naive Bayes" width="90" x="112" y="75"/>
<connect from_port="input 1" to_op="Naive Bayes" to_port="training set"/>
<connect from_op="Naive Bayes" from_port="model" to_port="output 1"/>
<connect from_op="Naive Bayes" from_port="exampleSet" to_port="output 2"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="source_input 3" spacing="0"/>
<portSpacing port="sink_output 1" spacing="0"/>
<portSpacing port="sink_output 2" spacing="0"/>
<portSpacing port="sink_output 3" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="k_nn" compatibility="5.3.015" expanded="true" height="76" name="k-NN" width="90" x="45" y="75"/>
<connect from_port="input 1" to_op="k-NN" to_port="training set"/>
<connect from_op="k-NN" from_port="model" to_port="output 1"/>
<connect from_op="k-NN" from_port="exampleSet" to_port="output 2"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="source_input 3" spacing="0"/>
<portSpacing port="sink_output 1" spacing="0"/>
<portSpacing port="sink_output 2" spacing="0"/>
<portSpacing port="sink_output 3" spacing="0"/>
</process>
<process expanded="true">
<connect from_port="input 1" to_port="output 1"/>
<connect from_port="input 2" to_port="output 2"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="source_input 3" spacing="0"/>
<portSpacing port="sink_output 1" spacing="0"/>
<portSpacing port="sink_output 2" spacing="0"/>
<portSpacing port="sink_output 3" spacing="0"/>
</process>
</operator>
<connect from_port="training" to_op="Select Subprocess" to_port="input 1"/>
<connect from_op="Select Subprocess" from_port="output 1" to_port="model"/>
<connect from_op="Select Subprocess" from_port="output 2" to_port="through 1"/>
<portSpacing port="source_training" 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="5.3.015" expanded="true" height="76" name="Apply Model (3)" width="90" x="45" y="120">
<list key="application_parameters"/>
</operator>
<operator activated="true" class="performance_classification" compatibility="5.3.015" expanded="true" height="76" name="Performance (3)" width="90" x="313" y="120">
<parameter key="root_mean_squared_error" value="true"/>
<parameter key="correlation" 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 (3)" to_port="labelled data"/>
<connect from_op="Performance (3)" from_port="performance" to_port="averagable 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_averagable 1" spacing="0"/>
<portSpacing port="sink_averagable 2" spacing="0"/>
</process>
</operator>
<connect from_port="input 1" to_op="Validation (3)" to_port="training"/>
<connect from_op="Validation (3)" from_port="model" to_port="output 1"/>
<connect from_op="Validation (3)" from_port="training" to_port="output 2"/>
<connect from_op="Validation (3)" from_port="averagable 1" to_port="output 3"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="source_input 2" spacing="0"/>
<portSpacing port="sink_output 1" spacing="0"/>
<portSpacing port="sink_output 2" spacing="0"/>
<portSpacing port="sink_output 3" spacing="0"/>
<portSpacing port="sink_output 4" spacing="0"/>
</process>
</operator>
<connect from_op="Retrieve Data2001" from_port="output" to_op="Replace Missing Values" to_port="example set input"/>
<connect from_op="Replace Missing Values" from_port="example set output" to_op="Optimize Selection (Evolutionary)" to_port="example set in"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="example set out" to_op="Loop" to_port="input 1"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="weights" to_port="result 1"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="performance" to_port="result 5"/>
<connect from_op="Loop" from_port="output 1" to_port="result 2"/>
<connect from_op="Loop" from_port="output 2" to_port="result 3"/>
<connect from_op="Loop" from_port="output 3" to_port="result 4"/>
<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"/>
</process>
</operator>
</process>
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.3.015">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.3.015" expanded="true" name="Process">
<process expanded="true">
<operator activated="true" class="retrieve" compatibility="5.3.015" expanded="true" height="60" name="Retrieve Data_2001_Selected" width="90" x="45" y="210">
<parameter key="repository_entry" value="../Data/Data_2001_Selected"/>
</operator>
<operator activated="true" class="apply_model" compatibility="5.3.015" expanded="true" height="76" name="Apply Model" width="90" x="581" y="30">
<list key="application_parameters"/>
</operator>
<operator activated="true" class="performance_classification" compatibility="5.3.015" expanded="true" height="76" name="Performance" width="90" x="715" y="30">
<list key="class_weights"/>
</operator>
<operator activated="true" class="numerical_to_binominal" compatibility="5.3.015" expanded="true" height="76" name="Numerical to Binominal" width="90" x="246" y="75"/>
<operator activated="true" class="fp_growth" compatibility="5.3.015" expanded="true" height="76" name="FP-Growth" width="90" x="514" y="210">
<parameter key="min_support" value="0.99"/>
</operator>
<operator activated="true" class="create_association_rules" compatibility="5.3.015" expanded="true" height="76" name="Create Association Rules" width="90" x="648" y="390">
<parameter key="min_confidence" value="0.95"/>
</operator>
<connect from_op="Retrieve Data_2001_Selected" from_port="output" to_op="Numerical to Binominal" to_port="example set input"/>
<connect from_op="Numerical to Binominal" from_port="example set output" to_op="FP-Growth" to_port="example set"/>
<connect from_op="FP-Growth" from_port="example set" to_port="result 1"/>
<connect from_op="FP-Growth" from_port="frequent sets" to_op="Create Association Rules" to_port="item sets"/>
<connect from_op="Create Association Rules" from_port="rules" 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>
Sorry my message be extensive.
Can you help me with this issue please? How to calculate root mean squared error in association rules?
Regards,
flaviorrl
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