train_valid_test_split: train_valid_test_split Splits feature and target data frames...

In UBC-MDS/PrepR: Makes Preprocessing Easier

Description

train_valid_test_split Splits feature and target data frames into random train, validation and test subsets The proportion of the train set relative to the input data will be valid_size * (1 - test_size)

Usage

train_valid_test_split(x, y, test_size = 0.25, valid_size = 0.25,
  shuffle = TRUE, random_state = NULL)

Arguments

x	(data frame) Original features from data set
y	(data frame) Original labels from data set
test_size	(double, default = NULL) Value between 0.0 and 1.0 to represent the proportion of the dataset to comprise the size of the test subset
valid_size	float or None (default = 0.25) Value between 0.0 and 1.0 to represent the proportion of the dataset to comprise the size of the test subset
shuffle	(default = TRUE) Shuffle the rows or not
random_state	(int, default = NULL) Seed for the random number generator

Value

list

Examples

x = data.frame('X1'=c(0,1,2,3,4,5,6,7),
               'X2'=c(8,9,10,11,12,13,14,15))

y = data.frame('Y'=c(0,1,2,3,4,5,6,7))


train_valid_test_split(x,y)$x_train
train_valid_test_split(x,y)$x_valid
train_valid_test_split(x,y)$x_test
train_valid_test_split(x,y)$y_train
train_valid_test_split(x,y)$y_valid
train_valid_test_split(x,y)$y_test

UBC-MDS/PrepR documentation built on April 2, 2020, 3:55 a.m.