squaredloss Class Reference

Inheritance diagram for squaredloss:

Public Member Functions
std::string	getType ()
float	getLoss (shared_data *sd, float prediction, float label)
float	getUpdate (float prediction, float label, float update_scale, float pred_per_update)
float	getUnsafeUpdate (float prediction, float label, float update_scale)
float	getRevertingWeight (shared_data *sd, float prediction, float eta_t)
float	getSquareGrad (float prediction, float label)
float	first_derivative (shared_data *sd, float prediction, float label)
float	second_derivative (shared_data *sd, float prediction, float)
Public Member Functions inherited from loss_function
virtual	~loss_function ()

Detailed Description

Definition at line 15 of file loss_functions.cc.

Member Function Documentation

first_derivative()

float squaredloss::first_derivative ( shared_data *  sd, float  prediction, float  label  )

inlinevirtual

Implements loss_function.

Definition at line 66 of file loss_functions.cc.

References shared_data::max_label, and shared_data::min_label.

Referenced by hingeloss::getSquareGrad(), logloss::getSquareGrad(), and quantileloss::getSquareGrad().

  {
    if (prediction < sd->min_label)
      prediction = sd->min_label;
    else if (prediction > sd->max_label)
      prediction = sd->max_label;
    return 2.f * (prediction - label);
  }

getLoss()

float squaredloss::getLoss ( shared_data *  sd, float  prediction, float  label  )

inlinevirtual

Implements loss_function.

Definition at line 20 of file loss_functions.cc.

References shared_data::max_label, and shared_data::min_label.

  {
    if (prediction <= sd->max_label && prediction >= sd->min_label)
    {
      float example_loss = (prediction - label) * (prediction - label);
      return example_loss;
    }
    else if (prediction < sd->min_label)
      if (label == sd->min_label)
        return 0.;
      else
        return (float)((label - sd->min_label) * (label - sd->min_label) +
            2. * (label - sd->min_label) * (sd->min_label - prediction));
    else if (label == sd->max_label)
      return 0.;
    else
      return float((sd->max_label - label) * (sd->max_label - label) +
          2. * (sd->max_label - label) * (prediction - sd->max_label));
  }

getRevertingWeight()

float squaredloss::getRevertingWeight ( shared_data *  sd, float  prediction, float  eta_t  )

inlinevirtual

Implements loss_function.

Definition at line 58 of file loss_functions.cc.

References shared_data::max_label, and shared_data::min_label.

  {
    float t = 0.5f * (sd->min_label + sd->max_label);
    float alternative = (prediction > t) ? sd->min_label : sd->max_label;
    return log((alternative - prediction) / (alternative - t)) / eta_t;
  }

getSquareGrad()

float squaredloss::getSquareGrad ( float  prediction, float  label  )

inlinevirtual

Implements loss_function.

Definition at line 65 of file loss_functions.cc.

{ return 4.f * (prediction - label) * (prediction - label); }

getType()

std::string squaredloss::getType ( )

inlinevirtual

Implements loss_function.

Definition at line 18 of file loss_functions.cc.

{ return "squared"; }

getUnsafeUpdate()

float squaredloss::getUnsafeUpdate ( float  prediction, float  label, float  update_scale  )

inlinevirtual

Implements loss_function.

Definition at line 53 of file loss_functions.cc.

  {
    return 2.f * (label - prediction) * update_scale;
  }

getUpdate()

float squaredloss::getUpdate ( float  prediction, float  label, float  update_scale, float  pred_per_update  )

inlinevirtual

Implements loss_function.

Definition at line 40 of file loss_functions.cc.

References correctedExp, and f.

  {
    if (update_scale * pred_per_update < 1e-6)
    {
      /* When exp(-eta_t)~= 1 we replace 1-exp(-eta_t)
       * with its first order Taylor expansion around 0
       * to avoid catastrophic cancellation.
       */
      return 2.f * (label - prediction) * update_scale;
    }
    return (label - prediction) * (1.f - correctedExp(-2.f * update_scale * pred_per_update)) / pred_per_update;
  }

second_derivative()

float squaredloss::second_derivative ( shared_data *  sd, float  prediction, float    )

inlinevirtual

Implements loss_function.

Definition at line 74 of file loss_functions.cc.

References shared_data::min_label.

  {
    if (prediction <= sd->max_label && prediction >= sd->min_label)
      return 2.;
    else
      return 0.;
  }

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The documentation for this class was generated from the following file:

• /mnt/c/w/linux/vowpal_wabbit/vowpalwabbit/loss_functions.cc