How to resolve the join operator problem?

emilie · February 17

Hi I am a beginner, I encountered join operator problem. After I installed extensions, my join operator still cannot show right port data except the id attribute, how to fix this problem? Thanks

emilie · February 17

Hello Roland You're genius. This is my first time seeking help online, I am impressive with your timeliness of your response and your unbelievable professional skill. Thank you so much!

RolandJones · February 17

Hi @emilie

Could you possibly post screenshots of what you're seeing, and if possible share the datasets? Otherwise, I'd suggest at looking at the Join operator tutorials to understand where the possible issues are coming from.

Best,
Roland

emilie · February 17

Hi Roland

Thank you for your reply. Here are my screenshots. The first one is left port input data, the second one is the right port input data, then the process and the output data. The output data only shows the id attribute from right port without other attributes, that's my problem as I'd like to compare the LOF_outlier from left port and the Distance_outlier from the right port. I already installed extensions. I didn't get any inspiration from the tutorial. Can you identify the reason for me? Thanks!

Emilie

Image: https://us.v-cdn.net/6030995/uploads/editor/hn/shkxvvk9wt06.png

Image: https://us.v-cdn.net/6030995/uploads/editor/a2/zpxraov1vx6l.png

Image: https://us.v-cdn.net/6030995/uploads/editor/mj/kw5jcoz4kmkx.png

Image: https://us.v-cdn.net/6030995/uploads/editor/n2/5ksnlkbdt6fq.png

RolandJones · February 17

Hi @emilie,

Do the variables of interest in the two tables have the same name? RapidMiner doesn't allow columns with the same name and I can see on the Join operator you have the option ticked on to remove double attributes, rather than rename.

Best,
Roland

emilie · February 17

They left and right port are from the same dataset, they have same name except the generated outlier by detect outlier (LOF) and detect outlier (Distances) which are renamed. I only need the LOF_outlier and Distances_outlier.

RolandJones · February 17

Hi @emilie,

I have discovered the cause by building a small sample. Because the columns of interest are classed as metadata (shown in yellow), only the metadata columns from the left table are carried forward. You can get round this by manually setting the columns to be regular or labels with a Set Role operator before you use the Join. I've attached my example underneath - let me know if this doesn't make sense.

Best,
Roland

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    <input/>

    <output/>

    <macros/>

  </context>

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    <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="subprocess" compatibility="10.3.001" expanded="true" height="82" name="Generate DataSet" origin="GENERATED_TUTORIAL" width="90" x="45" y="34">

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            <parameter key="number_of_examples" value="100"/>

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            <parameter key="add_id_attribute" value="false"/>

            <list key="numeric_series_configuration"/>

            <list key="date_series_configuration"/>

            <list key="date_series_configuration (interval)"/>

            <parameter key="date_format" value="yyyy-MM-dd HH:mm:ss"/>

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Ear_right&#10;0.7067359174595279 0.7877465869835184 Ear_right&#10;0.7394233664811464 0.7860259050967145 Ear_right&#10;0.749466614165472 0.7328131832071315 Ear_right&#10;0.8248418521018915 0.7134157163726719 Ear_right&#10;0.8239586646098369 0.7675190168773441 Ear_right&#10;0.8155149407204317 0.7135170163641819 Ear_right&#10;0.7856914234307533 0.6819138433217659 Ear_right&#10;0.708266829777928 0.7612342280212532 Ear_right&#10;0.290949977617754 0.8557666871174766 Noise&#10;0.7500676018742642 0.897027660749859 Noise&#10;0.040554927744786196 0.5072400792452862 Noise&#10;0.8351619113805846 0.13894038814840037 Noise&#10;0.17474033164278335 0.3636861115238198 Noise&#10;0.15150612475114178 0.8765856628207388 Noise&#10;0.8603082847506063 0.6338333996208041 Noise&#10;0.8620825903226392 0.5918053842487218 Noise&#10;0.9160298083819269 0.523390593285425 Noise&#10;0.42732547274373656 0.8337665738193867 Noise"/>

            <parameter key="column_separator" value=" "/>

            <parameter key="parse_all_as_nominal" value="false"/>

            <parameter key="decimal_point_character" value="."/>

            <parameter key="trim_attribute_names" value="true"/>

          </operator>

          <operator activated="true" class="set_role" compatibility="10.3.001" expanded="true" height="82" name="Set Role" origin="GENERATED_TUTORIAL" width="90" x="313" y="34">

            <parameter key="attribute_name" value="part"/>

            <parameter key="target_role" value="part"/>

            <list key="set_additional_roles"/>

          </operator>

          <connect from_op="Create ExampleSet" from_port="output" to_op="Set Role" to_port="example set input"/>

          <connect from_op="Set Role" from_port="example set output" to_port="out 1"/>

          <portSpacing port="source_in 1" spacing="0"/>

          <portSpacing port="sink_out 1" spacing="0"/>

          <portSpacing port="sink_out 2" spacing="0"/>

        </process>

        <description align="center" color="transparent" colored="false" width="126">Generate Mouse Data set</description>

      </operator>

      <operator activated="true" class="blending:generate_id" compatibility="10.3.001" expanded="true" height="82" name="Generate ID" width="90" x="179" y="34">

        <parameter key="create_nominal_ids" value="false"/>

        <parameter key="offset" value="0"/>

      </operator>

      <operator activated="true" class="detect_outlier_lof" compatibility="10.3.001" expanded="true" height="82" name="Detect Outlier (LOF)" width="90" x="313" y="34">

        <parameter key="minimal_points_lower_bound" value="10"/>

        <parameter key="minimal_points_upper_bound" value="20"/>

        <parameter key="distance_function" value="euclidian distance"/>

      </operator>

      <operator activated="true" class="anomalydetection:generate_anomaly_flag" compatibility="4.1.001" expanded="true" height="103" name="Generate Outlier Flag" width="90" x="514" y="34">

        <parameter key="method" value="manual"/>

        <parameter key="define_score_column" value="true"/>

        <parameter key="score_column" value="outlier"/>

        <parameter key="contamination_threshold" value="0.05"/>

        <parameter key="manual_threshold" value="1.0"/>

        <parameter key="zscore_threshold" value="3.0"/>

      </operator>

      <operator activated="true" class="detect_outlier_distances" compatibility="10.3.001" expanded="true" height="82" name="Detect Outlier (Distances)" width="90" x="313" y="187">

        <parameter key="number_of_neighbors" value="10"/>

        <parameter key="number_of_outliers" value="10"/>

        <parameter key="distance_function" value="euclidian distance"/>

      </operator>

      <operator activated="true" class="blending:set_role" compatibility="10.3.001" expanded="true" height="82" name="Set Role (2)" width="90" x="514" y="187">

        <list key="set_roles">

          <parameter key="outlier" value="regular"/>

        </list>

      </operator>

      <operator activated="true" class="concurrency:join" compatibility="10.3.001" expanded="true" height="82" name="Join" width="90" x="849" y="34">

        <parameter key="remove_double_attributes" value="false"/>

        <parameter key="join_type" value="inner"/>

        <parameter key="use_id_attribute_as_key" value="false"/>

        <list key="key_attributes">

          <parameter key="id" value="id"/>

        </list>

        <parameter key="keep_both_join_attributes" value="false"/>

      </operator>

      <connect from_op="Generate DataSet" from_port="out 1" to_op="Generate ID" to_port="example set input"/>

      <connect from_op="Generate ID" from_port="example set output" to_op="Detect Outlier (LOF)" to_port="example set input"/>

      <connect from_op="Detect Outlier (LOF)" from_port="example set output" to_op="Generate Outlier Flag" to_port="example set"/>

      <connect from_op="Detect Outlier (LOF)" from_port="original" to_op="Detect Outlier (Distances)" to_port="example set input"/>

      <connect from_op="Generate Outlier Flag" from_port="example set" to_op="Join" to_port="left"/>

      <connect from_op="Detect Outlier (Distances)" 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="Join" to_port="right"/>

      <connect from_op="Join" from_port="join" 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"/>

      <description align="center" color="yellow" colored="false" height="68" resized="true" width="178" x="484" y="282">Turn this operator off to see the difference</description>

    </process>

  </operator>

</process>

emilie · February 17

Hello Roland You're genius. This is my first time seeking help online, I am impressive with your timeliness of your response and your unbelievable professional skill. Thank you so much!

How to resolve the join operator problem?

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