Targetrelated

Targetrelated is a term used in statistics and machine learning to describe features, signals, or variables that are directly or indirectly related to a predictive target variable. The concept emphasizes that not all inputs contribute equally to a model's outcome; targetrelated features are those with a meaningful relationship to the target.

Definition and scope. Targetrelated can include direct causes, mediating variables, confounders, and proxy measures that help explain the target. They may also capture contextual information that shapes the target. Features that are unrelated or redundant are considered non-targetrelated.

Examples. In a housing price model, targetrelated features include square footage, location, age, and recent comparable sales. In demand forecasting, promotions, seasonality, and lagged demand are targetrelated. In medical prognosis, vital signs and lab results that correlate with the outcome are targetrelated.

Identification and handling. Practical methods to identify targetrelated features include computing correlations, mutual information, feature importance from models, and model-agnostic explanations. Causal discovery can help distinguish true drivers from mere associations. When assembling data, beware of leakage: including information that would not be available at prediction time can render features incorrectly targetrelated and degrade model generalization.