EvaluationMeasures.Precision {EvaluationMeasures}

R Documentation

EvaluationMeasures.Precision

Description

Precision of prediction

Usage

EvaluationMeasures.Precision(Real = NULL, Predicted = NULL, Positive = 1,
  TP = NULL, TN = NULL, FP = NULL, FN = NULL)

Arguments

Real	Real binary values of the class
Predicted	Predicted binary values of the class
Positive	Consider 1 label as Positive Class unless changing this parameter to 0
TP	Number of True Positives. Number of 1 in real which is 1 in predicted.
TN	Number of True Negatives. Number of 0 in real which is 0 in predicted.
FP	Number of False Positives. Number of 0 in real which is 1 in predicted.
FN	Number of False Negatives. Number of 1 in real which is 0 in predicted.

Details

Precision is What fraction of positive predicted are real positive.

By getting the predicted and real values or number of TP,TN,FP,FN return the Precision or Positive Predicted Value of model

Value

Precision

Author(s)

Babak Khorsand

Examples

EvaluationMeasures.Precision(c(1,0,1,0,1,0,1,0),c(1,1,1,1,1,1,0,0))

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