Score_algorithms_interval: Score a vector of error metrics for algorithms by the...

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

Description

Score a vector of error metrics for algorithms by the interval

Usage

Score_algorithms_interval(
  x,
  trim = FALSE,
  reward.punishment = TRUE,
  decreasing = TRUE,
  hundred.percent = FALSE
)

Arguments

x	Input vector of error metrics (NA values are allowed)
trim	whether to run a trim process to calculate mean and standard deviation of input vector x (Default as FALSE)
reward.punishment	Whether to conduct the reward and punishment mechanism in scoring system (Default as TRUE)
decreasing	the order of the good metric to be evaluated. For instance, MAE should use decreasing = TRUE (Default) since the algorithm performs better when MAE becomes smaller. However, when comes to Rsquare from linear regression (maximum is 1), it should be FALSE
hundred.percent	A variable constrain for metrics that the maximun of input x should not be greater than 100.

Value

Results of Score_algorithms_interval() are returned as a list including:

p	A ggplot list of the scoring result.
score	The final score from by the interval score.
u	Trimmed mean of input x with NA values removed.
bds	Up and low boundaries for determining scores.
x	The input x.

See Also

Other Algorithm assessment: Assessment_via_cluster(), Getting_Asses_results(), Sampling_via_cluster(), Score_algorithms_sort(), Scoring_system()

Examples

set.seed(1234)
x = runif(10)
result = Score_algorithms_interval(x)

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