confusion.matrix.markedness.simple: Confusion Matrix Measures - Markedness

In burrm/lolcat: Miscellaneous Useful Functions

Confusion Matrix Measures - Markedness

Description

Calculate Markedness, defined as PPV+NPV-1, for a given confusion matrix.

Usage

confusion.matrix.markedness(confusion.matrix)

confusion.matrix.markedness.simple(
  true.positive = 0,
  false.positive = 1,
  true.negative = 0,
  false.negative = 1,
  positive.predictive.value =
    confusion.matrix.positive.predictive.value.simple(true.positive = true.positive,
    false.positive = false.positive),
  negative.predictive.value =
    confusion.matrix.negative.predictive.value.simple(true.negative = true.negative,
    false.negative = false.negative)
)

Arguments

confusion.matrix	Matrix - confusion matrix.
true.positive	Scalar - Cases identified as true positive - optional if PPV specified
false.positive	Scalar - Cases identified as false positive - optional if PPV specified
true.negative	Scalar - Cases identified as true negative - optional if NPV specified
false.negative	Scalar - Cases identified as false negative - optional if NPV specified
positive.predictive.value	Scalar - Positive Predictive Value (PPV) - optional if true.positive and false.positive parameters are used.
negative.predictive.value	Scalar - Negative Predictive Value (NPV) - optional if true.negative and false.negative parameters are used.

Value

A scalar with computed value.

burrm/lolcat documentation built on Sept. 15, 2023, 11:35 a.m.