cal.metrics.vector: Assess the performance of algorithms as vector

In bishun945/FCMm: Fuzzy Cluster Method Based on the Optimized m Value (Fuzzifier)

Description

Assess the performance of algorithms as vector

Usage

cal.metrics.vector(
  x,
  y,
  name = "all",
  log10 = FALSE,
  c.value = mean(x, na.rm = TRUE)
)

cal.metrics.vector.names()

Arguments

x	True value OR Actual value
y	Estimated value OR Predict value
name	The name of metrics
log10	Logical. Whether the input x and y should be log10-transformed
c.value	Compensated value for CMAPE and CMRPE. Default is the mean of x.

Value

Result of cal.metrics.vector is a list of selected metric values.

The call of cal.metrics.vector.names retunrs the metrics names in cal.metrics.vector

See Also

Other Utils: SRF_simulate(), cal.metrics(), level_to_variable(), trim_sd()

Examples

x = runif(100)
y = runif(100)
result = cal.metrics.vector(x,y)

bishun945/FCMm documentation built on Oct. 15, 2021, 6:43 p.m.