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I'am ML newbie but I decided to create a program in ML.NET for data classification. However, my dataset has a very large number of columns, so I'll use another example.

There is an iris database with five columns:

  • sepalLength (number)
  • sepalWidth (number)
  • petalWidth (number)
  • petalWidth (number)
  • irisClass (predicted -> Iris-setosa/Iris-versicolor/Iris-virginica)

Is it possible to investigate to what extent a given data column influences the classification of a flower to a given type of iris? For example, the value of the sepalLength column influences the result by 60%, while the value of the petalWidth column influences the result by 5%.

molbdnilo
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Adam Wróbel
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1 Answers1

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I think what you're looking for is either permutation feature importance or feature contribution calculation

Luis Quintanilla
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