Better still is not to impute anything but rather to leave it up to each model's perspective how to treat missing values. For example "distance functions" can be customised and in some cases asymmetric (e.g. reflecting some aspect of the application domain). Preprocessing data presupposes downstream purposes (that might change over time).
Better still is not to impute anything but rather to leave it up to each model's perspective how to treat missing values. For example "distance functions" can be customised and in some cases asymmetric (e.g. reflecting some aspect of the application domain). Preprocessing data presupposes downstream purposes (that might change over time).
Better still is not to impute anything but rather to leave it up to each model's perspective how to treat missing values. For example "distance functions" can be customised and in some cases asymmetric (e.g. reflecting some aspect of the application domain). Preprocessing data presupposes downstream purposes (that might change over time).