title: Explanatory variables when classifying multivariate time series data using decision trees in seglearn
body: <p>I am currently working on classifying multivariate time series data.
  <a href="https://dmbee.github.io/seglearn/auto_examples/plot_scoring.html#sphx-glr-auto-examples-plot-scoring-py" rel="nofollow noreferrer">https://dmbee.github.io/seglearn/auto_examples/plot_scoring.html#sphx-glr-auto-examples-plot-scoring-py</a>
  As a reference, I replaced the RandomForestClassifier with DecisionTreeClassifier, and it worked.
  But if I visualize this using export_graphviz (), <strong>what does the feature_names parameter mean?</strong></p>
  
  <p>Since it is time-series data, does it mean the position information of the time-series data?
  However, the input data is (50, 375, 18) three-dimensional data. The length of the time series data is 375 and has the values of 18 sensors. In this example, 50 input batches are used.</p>