| export_results {lares} | R Documentation |
Export h2o_automl's Results
Description
Export RDS, TXT, POJO, MOJO and all results from h2o_automl().
Usage
export_results(
results,
thresh = 10,
which = c("txt", "csv", "rds", "binary", "mojo", "plots", "dev", "production"),
note = NA,
subdir = NA,
save = TRUE,
seed = 0
)
Arguments
results |
|
thresh |
Integer. Threshold for selecting binary or regression models: this number is the threshold of unique values we should have in 'tag' (more than: regression; less than: classification) |
which |
Character vector. Select which file format to export: Possible values: txt, csv, rds, binary, mojo, plots. You might also use dev (txt, csv, rds) or production (binary, mojo) or simply don't use parameter to export everything |
note |
Character. Add a note to the txt file. Useful when lots of models are trained and saved to remember which one is which one |
subdir |
Character. In which directory do you wish to save the results? |
save |
Boolean. Do you wish to save/export results? |
seed |
Numeric. For reproducible results and random splits. |
Value
No return value, called for side effects.
See Also
Other Machine Learning:
ROC(),
conf_mat(),
gain_lift(),
h2o_automl(),
h2o_predict_MOJO(),
h2o_selectmodel(),
impute(),
iter_seeds(),
lasso_vars(),
model_metrics(),
model_preprocess(),
msplit()
Other Tools:
autoline(),
bind_files(),
bring_api(),
chr2num(),
db_download(),
db_upload(),
export_plot(),
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(),
msplit(),
myip(),
quiet(),
read.file(),
statusbar(),
tic(),
try_require(),
updateLares(),
warnifnot(),
what_size()