Feature selection for efficient modeling
- Speed up model building: by using only the most important variables in model building, feature selection enables us to significantly reduce processing times thereby speeding up model building. The greater the number of potential "input" variables, the greater is the improvement in model building speed by using feature selection.
- Reduction in time and cost of model building: collecting data for some variables is both time consuming and costly. Using feature selection, resources can be focused on collecting data for only the most important variables thereby eliminating waste of time and money on less important variables.
- Removing unimportant variables: some variables which appear to be important inputs to the model building process may turn out to have little or no predictive importance. Feature selection helps identify these variables so they can be excluded from the model building process upfront.
- Ease of deployment: simpler models with fewer input variables are easier to deploy and therefore more practical. This is perhaps the most important benefit of feature selection.