axe-kknn {butcher}R Documentation

Axing an kknn.

Description

kknn objects are created from the kknn package, which is utilized to do weighted k-Nearest Neighbors for classification, regression and clustering.

Usage

## S3 method for class 'kknn'
axe_call(x, verbose = FALSE, ...)

## S3 method for class 'kknn'
axe_env(x, verbose = FALSE, ...)

## S3 method for class 'kknn'
axe_fitted(x, verbose = FALSE, ...)

Arguments

x

A model object.

verbose

Print information each time an axe method is executed. Notes how much memory is released and what functions are disabled. Default is FALSE.

...

Any additional arguments related to axing.

Value

Axed kknn object.

Examples


# Load libraries
library(parsnip)
library(rsample)
library(rpart)
library(kknn)

# Load data
set.seed(1234)
split <- initial_split(kyphosis, prop = 9/10)
spine_train <- training(split)

# Create model and fit
kknn_fit <- nearest_neighbor(mode = "classification",
                             neighbors = 3,
                             weight_func = "gaussian",
                             dist_power = 2) %>%
  set_engine("kknn") %>%
  fit(Kyphosis ~ ., data = spine_train)

out <- butcher(kknn_fit, verbose = TRUE)


# Another kknn model object
m <- dim(iris)[1]
val <- sample(1:m,
              size = round(m/3),
              replace = FALSE,
              prob = rep(1/m, m))
iris.learn <- iris[-val,]
iris.valid <- iris[val,]
kknn_fit <- kknn(Species ~ .,
                 iris.learn,
                 iris.valid,
                 distance = 1,
                 kernel = "triangular")
out <- butcher(kknn_fit, verbose = TRUE)



[Package butcher version 0.3.4 Index]