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. *