Mean_errors

class mlptrain.loss.mean_errors.MAD(method_name: str | None = None)

Bases: LossFunction

MAD = 1/N √(Σ_i |y_i^predicted - y_i^true|)

loss_type: alias of MADValue

static statistic(arr: ndarray) → float

class mlptrain.loss.mean_errors.MADValue(x, error: float | None = None): Bases: LossValue

class mlptrain.loss.mean_errors.RMSE(method_name: str | None = None)

Bases: _DeltaLossFunction

RMSE = √(1/N Σ_i (y_i^predicted - y_i^true)^2)

loss_type: alias of RMSEValue

static statistic(arr: ndarray) → float: Error measure over an array of values

class mlptrain.loss.mean_errors.RMSEValue(x, error: float | None = None): Bases: LossValue