How to Calculate Feature Importance With Python

 * Feature importance refers to a class of techniques for assigning scores to input features to a predictive model that indicates the relative importance of each feature when making a prediction.

* Feature importance scores can be calculated for problems that involve predicting a numerical value, called regression, and those problems that involve predicting a class label, called classification.

* Feature importance helps in :

  • Better understanding the data.
  • Better understanding a model.
  • Reducing the number of input features.
* There are many ways to calculate feature importance scores and many models that can be used for this purpose.


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