daltoolbox (version 1.3.767)

reg_lm: Linear regression (lm)

Description

Linear regression using stats::lm.

Usage

reg_lm(formula = NULL, attribute = NULL, features = NULL)

Value

returns a reg_lm object

Arguments

formula

optional regression formula (e.g., y ~ x1 + x2).

attribute

target attribute name (used when formula is NULL)

features

optional vector of feature names (used when formula is NULL)

Examples

if (requireNamespace("MASS", quietly = TRUE)) {
 data(Boston, package = "MASS")

 # Simple linear regression
 model_simple <- reg_lm(formula = medv ~ lstat)
 model_simple <- fit(model_simple, Boston)
 pred_simple <- predict(model_simple, Boston)
 eval_simple <- evaluate(model_simple, Boston$medv, pred_simple)
 eval_simple$metrics

 # Polynomial regression (degree 2)
 model_poly <- reg_lm(formula = medv ~ poly(lstat, 2, raw = TRUE))
 model_poly <- fit(model_poly, Boston)
 pred_poly <- predict(model_poly, Boston)
 eval_poly <- evaluate(model_poly, Boston$medv, pred_poly)
 eval_poly$metrics

 # Multiple regression
 model_multi <- reg_lm(formula = medv ~ lstat + rm + ptratio)
 model_multi <- fit(model_multi, Boston)
 pred_multi <- predict(model_multi, Boston)
 eval_multi <- evaluate(model_multi, Boston$medv, pred_multi)
 eval_multi$metrics
}