split_random {RSSL} | R Documentation |
Randomly split dataset in multiple parts
Description
The data.frame should start with a vector containing labels, or formula should be defined.
Usage
split_random(df, formula = NULL, splits = c(0.5, 0.5), min_class = 0)
Arguments
df |
data.frame; Data frame of interest |
formula |
formula; Formula to indicate the outputs |
splits |
numeric; Probability of of assigning to each part, automatically normalized, should be >1 |
min_class |
integer; minimum number of objects per class in each part |
Value
list of data.frames
See Also
Other RSSL utilities:
LearningCurveSSL()
,
SSLDataFrameToMatrices()
,
add_missinglabels_mar()
,
df_to_matrices()
,
measure_accuracy()
,
missing_labels()
,
split_dataset_ssl()
,
true_labels()
Examples
library(dplyr)
df <- generate2ClassGaussian(200,d=2)
dfs <- df %>% split_random(Class~.,split=c(0.5,0.3,0.2),min_class=1)
names(dfs) <- c("Train","Validation","Test")
lapply(dfs,summary)
[Package RSSL version 0.9.7 Index]