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transform data to series

walidos07walidos07 Member Posts: 2 Contributor I
edited August 2019 in Help
my data are defined as follows:
Sample T1 T2 T3 T4
S1 s11 s12 s13 s14
S2 s21 s22 s23 s24
S3 s31 s32 s33 s34
Each line is a time series data.
my question:how to transform my data to use series operators such as discrete wavelet transform for each instance s1, s2 and s3.
thank you for your help


  • Options
    awchisholmawchisholm RapidMiner Certified Expert, Member Posts: 458 Unicorn
    Here's an example that you could use as a basis.

    <?xml version="1.0" encoding="UTF-8" standalone="no"?>
    <process version="5.0">
      <operator activated="true" class="process" compatibility="5.0.8" expanded="true" name="Process">
        <process expanded="true" height="521" width="614">
          <operator activated="true" class="series:generate_example_set_series" compatibility="5.0.2" expanded="true" height="60" name="Generate Data (Series)" width="90" x="45" y="75">
            <parameter key="number_of_examples" value="200"/>
            <parameter key="number_of_frequencies" value="1"/>
          <operator activated="true" class="series:process_series" compatibility="5.0.2" expanded="true" height="76" name="Process Series" width="90" x="179" y="75">
            <parameter key="start_attribute" value="att0"/>
            <parameter key="end_attribute" value="att512"/>
            <process expanded="true" height="716" width="707">
              <operator activated="true" class="series:window_transformation" compatibility="5.0.2" expanded="true" height="60" name="Window Transformation" width="90" x="45" y="75">
                <parameter key="function_type" value="Bartlett"/>
              <operator activated="true" class="series:discrete_fourier_transformation" compatibility="5.0.2" expanded="true" height="60" name="Discrete Fourier Transformation" width="90" x="179" y="75"/>
              <operator activated="true" class="series:extract_peak" compatibility="5.0.2" expanded="true" height="60" name="Extract Peak" width="90" x="313" y="75">
                <parameter key="number_of_peaks" value="1"/>
              <connect from_port="series" to_op="Window Transformation" to_port="series"/>
              <connect from_op="Window Transformation" from_port="series" to_op="Discrete Fourier Transformation" to_port="series"/>
              <connect from_op="Discrete Fourier Transformation" from_port="series" to_op="Extract Peak" to_port="series"/>
              <connect from_op="Extract Peak" from_port="series" to_port="series"/>
              <portSpacing port="source_series" spacing="0"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="sink_series" spacing="0"/>
          <operator activated="true" class="x_validation" compatibility="5.0.0" expanded="true" height="112" name="Validation" width="90" x="380" y="75">
            <description>A cross validation including a linear regression.</description>
            <process expanded="true" height="654" width="466">
              <operator activated="true" class="support_vector_machine" compatibility="5.0.8" expanded="true" height="112" name="SVM" width="90" x="188" y="30"/>
              <connect from_port="training" to_op="SVM" to_port="training set"/>
              <connect from_op="SVM" 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 expanded="true" height="654" width="466">
              <operator activated="true" class="apply_model" compatibility="5.0.0" expanded="true" height="76" name="Apply Model" width="90" x="45" y="30">
                <list key="application_parameters"/>
              <operator activated="true" class="performance" compatibility="5.0.0" expanded="true" height="76" name="Performance" width="90" x="179" y="30"/>
              <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" to_port="labelled data"/>
              <connect from_op="Performance" 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"/>
          <connect from_op="Generate Data (Series)" from_port="output" to_op="Process Series" to_port="example set"/>
          <connect from_op="Process Series" from_port="example set" to_op="Validation" to_port="training"/>
          <connect from_op="Validation" from_port="model" to_port="result 1"/>
          <connect from_op="Validation" from_port="averagable 1" 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"/>
  • Options
    wesselwessel Member Posts: 537 Maven
    This example is really good.

    Do you have more examples?

    I hardly ever use: "Process Series" because I don't understand how it works.
    But it seems really powerful.
  • Options
    awchisholmawchisholm RapidMiner Certified Expert, Member Posts: 458 Unicorn

    There are a few more examples on my blog

  • Options
    wesselwessel Member Posts: 537 Maven
    I don't understand how to download those .xml files on your blog.
  • Options
    awchisholmawchisholm RapidMiner Certified Expert, Member Posts: 458 Unicorn
    For reasons I can't remember now, I keep all the files in Google Docs and it's too late to change now.

    Keep following the links until you find them.

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