Boots_CI: Confidence Interval using Bootstrap

In kerntools: Kernel Functions and Tools for Machine Learning Applications

Confidence Interval using Bootstrap

Description

'Boots_CI()' computes the Confidence Interval (CI) of a performance measure (for instance, accuracy) via bootstrapping.

Usage

Boots_CI(target, pred, index = "acc", nboots, confidence = 95, ...)

Arguments

target	Numeric vector containing the actual values.
pred	Numeric vector containing the predicted values. (The order should be the same than the target's).
index	Performance measure name, in lowercase. (Defaults: "acc").
nboots	Number of bootstrapping replicas.
confidence	Confidence level; for instance, 95% or 99%. (Defaults: 95).
...	Further arguments to be passed to the performance measures functions; notably, multi.class="macro" or multi.class="micro" for the macro or micro performance measures. (Defaults: "macro").

Value

A vector containing the bootstrap estimate of the performance and its CI.

Examples

y <- c(rep("a",30),rep("b",20))
y_pred <- c(rep("a",20),rep("b",30))
# Computing Accuracy with their 95%CI
Boots_CI(target=y, pred=y_pred, index="acc", nboots=1000, confidence=95)

kerntools documentation built on April 3, 2025, 7:52 p.m.