| msplit {lares} | R Documentation |
Split a dataframe for training and testing sets
Description
This function splits automatically a dataframe into train and test datasets. You can define a seed to get the same results every time, but has a default value. You can prevent it from printing the split counter result.
Usage
msplit(df, size = 0.7, seed = 0, print = TRUE)
Arguments
df |
Dataframe |
size |
Numeric. Split rate value, between 0 and 1. If set to 1, the train and test set will be the same. |
seed |
Integer. Seed for random split |
print |
Boolean. Print summary results? |
Value
List with both datasets, summary, and split rate.
See Also
Other Machine Learning:
ROC(),
conf_mat(),
export_results(),
gain_lift(),
h2o_automl(),
h2o_predict_MOJO(),
h2o_selectmodel(),
impute(),
iter_seeds(),
lasso_vars(),
model_metrics(),
model_preprocess()
Other Tools:
autoline(),
bind_files(),
bring_api(),
chr2num(),
db_download(),
db_upload(),
export_plot(),
export_results(),
files_functions(),
font_exists(),
formatColoured(),
formatHTML(),
get_credentials(),
glued(),
grepm(),
h2o_selectmodel(),
haveInternet(),
image_metadata(),
importxlsx(),
ip_data(),
json2vector(),
list_cats(),
listfiles(),
mail_send(),
markdown2df(),
move_files(),
myip(),
quiet(),
read.file(),
statusbar(),
tic(),
try_require(),
updateLares(),
warnifnot(),
what_size()
Examples
data(dft) # Titanic dataset
splits <- msplit(dft, size = 0.7, seed = 123)
names(splits)