smartdata (version 1.0.3)

clean_noise: Noise cleaning wrapper

Description

Noise cleaning wrapper

Usage

clean_noise(dataset, method, class_attr = "Class", ...)

Arguments

dataset

we want to clean noisy instances on

method

selected method of noise cleaning

class_attr

character. Indicates the class attribute or attributes from dataset. Must exist in it.

...

Further arguments for method

Value

The treated dataset (either with noisy instances replaced or erased)

Examples

# NOT RUN {
library("smartdata")
data(iris0, package = "imbalance")

super_iris <- clean_noise(iris, method = "AENN", class_attr = "Species", k = 3)
super_iris <- clean_noise(iris, "GE", class_attr = "Species", k = 5, relabel_th = 2)
super_iris <- clean_noise(iris, "HARF", class_attr = "Species",
                          num_folds = 10, agree_level = 0.7, num_trees = 5)

# }
# NOT RUN {
super_iris <- clean_noise(iris0, "TomekLinks")
super_iris <- clean_noise(iris, "hybrid", class_attr = "Species",
                          consensus = FALSE, action = "repair")
super_iris <- clean_noise(iris, "Mode", class_attr = "Species", type = "iterative",
                          action = "repair", epsilon = 0.05,
                          num_iterations = 200, alpha = 1, beta = 1)
super_iris <- clean_noise(iris, "INFFC", class_attr = "Species", consensus = FALSE,
                          prob_noisy = 0.2, num_iterations = 3, k = 5, threshold = 0)
super_iris <- clean_noise(iris, "IPF", class_attr = "Species", consensus = FALSE,
                          num_folds = 3, prob_noisy = 0.2,
                          prob_good = 0.5, num_iterations = 3)
super_iris <- clean_noise(iris, "ORBoost", class_attr = "Species",
                          num_boosting = 20, threshold = 11, num_adaboost = 20)
super_iris <- clean_noise(iris, "PF", class_attr = "Species", prob_noisy = 0.01,
                          num_iterations = 5, prob_good = 0.5, theta = 0.8)
super_iris <- clean_noise(iris, "C45robust", class_attr = "Species", num_folds = 5)
# }