Vector Linear Regression - Multi Label
Hello,
I'm trying to built a vector linear regression model with multiple label attributes, but I'm finding difficulties with the special role setup.
I read the vector linear regression description and from the below I understand that all labels must be named in its special role as something like "label_1", "label_2" and so on.
****The attributes forming the vector should be marked as special, the special role names of all label attributes should start with 'label'.*****
I'm sure that this must be easy, but whatever I've tried doesn't work.
Enclosed the example process and the data
Can you please shed some light on this?
Thanks
I'm trying to built a vector linear regression model with multiple label attributes, but I'm finding difficulties with the special role setup.
I read the vector linear regression description and from the below I understand that all labels must be named in its special role as something like "label_1", "label_2" and so on.
****The attributes forming the vector should be marked as special, the special role names of all label attributes should start with 'label'.*****
I'm sure that this must be easy, but whatever I've tried doesn't work.
Enclosed the example process and the data
Can you please shed some light on this?
Thanks
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Hi @sgenzer,
when in VLR operator's description says (see below) I have to confess that the plural on word label lead me to believe that this operator was capable of dealing with multi-label problems.
Can you please clarify that?
"It regresses all regular attributes upon a vector of labels. The attributes forming the vector should be marked as special, the special role names of all label attributes should start with 'label'."
Thanks,
Pedro
when in VLR operator's description says (see below) I have to confess that the plural on word label lead me to believe that this operator was capable of dealing with multi-label problems.
Can you please clarify that?
"It regresses all regular attributes upon a vector of labels. The attributes forming the vector should be marked as special, the special role names of all label attributes should start with 'label'."
Thanks,
Pedro
Altair Employeehi @Oprick in all honesty I have never used that operator in 6+ years of using the software. Never even seen it before. Looking at the tutorial it seems to function like the other learners but I do see what you're saying. I just opened up the source code on GitHub and it looks like our good friend @TobiasMalbrecht was the author back in the day. Maybe he has some insight... 
If you want multi-label modeling, I'd just use the multi-labeling modeling operator in the Ensembles folder. Open the tutorial and you will see how it works on Titanic.
Scott
If you want multi-label modeling, I'd just use the multi-labeling modeling operator in the Ensembles folder. Open the tutorial and you will see how it works on Titanic.
Scott
Hi @sgenzer, thanks for you help and pulling the Tobias into the thread.
I'm aware of multi-label indeed, but I have to say that I'm particular curious of this supposed capabilities of VLR.
Again thanks for your help,
Pedro
I'm aware of multi-label indeed, but I have to say that I'm particular curious of this supposed capabilities of VLR.
Again thanks for your help,
Pedro
Altair Employeefair enough @Oprick. You will have to wait for the maestro @TobiasMalbrecht to get back from vacation 
Hi @Oprick,
Try setting the role of the first label just to "label", the remainder ones to "label_2", "label_3", and so on. See attached process. This should work.
Hope this helps,
Tobias
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Hi @Oprick,
Try setting the role of the first label just to "label", the remainder ones to "label_2", "label_3", and so on. See attached process. This should work.
Hope this helps,
Tobias
<?xml version="1.0" encoding="UTF-8"?><process version="9.5.001"> <context> <input/> <output/> <macros/> </context> <operator activated="true" class="process" compatibility="9.5.001" 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="read_excel" compatibility="9.5.001" expanded="true" height="68" name="Read Excel" width="90" x="45" y="34"> <parameter key="excel_file" value="example.xlsx"/> <parameter key="sheet_selection" value="sheet number"/> <parameter key="sheet_number" value="1"/> <parameter key="imported_cell_range" value="A1"/> <parameter key="encoding" value="SYSTEM"/> <parameter key="first_row_as_names" value="true"/> <list key="annotations"/> <parameter key="date_format" value=""/> <parameter key="time_zone" value="SYSTEM"/> <parameter key="locale" value="English (United States)"/> <parameter key="read_all_values_as_polynominal" value="false"/> <list key="data_set_meta_data_information"> <parameter key="0" value="A.true.integer.attribute"/> <parameter key="1" value="B.true.integer.attribute"/> <parameter key="2" value="C.true.integer.attribute"/> <parameter key="3" value="D.true.integer.attribute"/> <parameter key="4" value="E.true.integer.attribute"/> <parameter key="5" value="year.true.integer.attribute"/> <parameter key="6" value="week.true.integer.attribute"/> <parameter key="7" value="air.true.real.attribute"/> <parameter key="8" value="mmp.true.real.attribute"/> <parameter key="9" value="total.true.integer.attribute"/> <parameter key="10" value="total+1.true.integer.attribute"/> <parameter key="11" value="label_A+1.true.integer.attribute"/> <parameter key="12" value="label_B+1.true.integer.attribute"/> <parameter key="13" value="label_C+1.true.integer.attribute"/> <parameter key="14" value="label_D+1.true.integer.attribute"/> <parameter key="15" value="label_E+1.true.integer.attribute"/> <parameter key="16" value="total-1.true.integer.attribute"/> <parameter key="17" value="total-2.true.integer.attribute"/> <parameter key="18" value="total-3.true.integer.attribute"/> <parameter key="19" value="A-1.true.integer.attribute"/> <parameter key="20" value="A-2.true.integer.attribute"/> <parameter key="21" value="A-3.true.integer.attribute"/> <parameter key="22" value="B-1.true.integer.attribute"/> <parameter key="23" value="B-2.true.integer.attribute"/> <parameter key="24" value="B-3.true.integer.attribute"/> <parameter key="25" value="C-1.true.integer.attribute"/> <parameter key="26" value="C-2.true.integer.attribute"/> <parameter key="27" value="C-3.true.integer.attribute"/> <parameter key="28" value="D-1.true.integer.attribute"/> <parameter key="29" value="D-2.true.integer.attribute"/> <parameter key="30" value="D-3.true.integer.attribute"/> <parameter key="31" value="E-1.true.integer.attribute"/> <parameter key="32" value="E-2.true.integer.attribute"/> <parameter key="33" value="E-3.true.integer.attribute"/> <parameter key="34" value="id.true.integer.attribute"/> </list> <parameter key="read_not_matching_values_as_missings" value="false"/> <parameter key="datamanagement" value="double_array"/> <parameter key="data_management" value="auto"/> </operator> <operator activated="true" class="set_role" compatibility="9.5.001" expanded="true" height="82" name="Set Role" width="90" x="179" y="34"> <parameter key="attribute_name" value="label_A+1"/> <parameter key="target_role" value="label"/> <list key="set_additional_roles"/> </operator> <operator activated="true" class="vector_linear_regression" compatibility="9.5.001" expanded="true" height="82" name="Vector Linear Regression" width="90" x="313" y="34"> <parameter key="use_bias" value="true"/> <parameter key="ridge" value="1.0E-8"/> </operator> <operator activated="true" class="apply_model" compatibility="9.5.001" expanded="true" height="82" name="Apply Model" width="90" x="447" y="34"> <list key="application_parameters"/> <parameter key="create_view" value="false"/> </operator> <connect from_op="Read Excel" from_port="output" to_op="Set Role" to_port="example set input"/> <connect from_op="Set Role" from_port="example set output" to_op="Vector Linear Regression" to_port="training set"/> <connect from_op="Vector Linear Regression" from_port="model" to_op="Apply Model" to_port="model"/> <connect from_op="Vector Linear Regression" from_port="exampleSet" to_op="Apply Model" to_port="unlabelled data"/> <connect from_op="Apply Model" from_port="labelled data" to_port="result 2"/> <connect from_op="Apply Model" from_port="model" to_port="result 1"/> <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>Scott