Create a new version of an existing experiment.
create_experiment_version(
experiment_id,
dataset_id = NULL,
target_column = NULL,
holdout_dataset_id = NULL,
id_column = NULL,
drop_list = NULL,
profile = NULL,
experiment_description = NULL,
metric = NULL,
fold_column = NULL,
normal_models = NULL,
lite_models = NULL,
simple_models = NULL,
with_blend = NULL,
weight_column = NULL,
features_engineering_selected_list = NULL,
features_selection_count = NULL,
features_selection_time = NULL,
folder_dataset_id = NULL,
filename_column = NULL,
ymin = NULL,
ymax = NULL,
xmin = NULL,
xmax = NULL,
time_column = NULL,
start_dw = NULL,
end_dw = NULL,
start_fw = NULL,
end_fw = NULL,
group_list = NULL,
apriori_list = NULL,
content_column = NULL,
queries_dataset_id = NULL,
queries_dataset_content_column = NULL,
queries_dataset_id_column = NULL,
queries_dataset_matching_id_description_column = NULL,
top_k = NULL,
lang = NULL,
models_params = NULL,
name = NULL,
onnx_file = NULL,
yaml_file = NULL
)id of the experiment that will host the new version.
id of the dataset used for the training phase.
name of the TARGET column.
id of the holdout dataset.
name of the id column.
list of names of features to drop.
chosen profil among "quick", "normal", "advanced".
experiment description.
name of the metric to optimise.
name of the fold column.
list of (normal) models to select with full FE & hyperparameters search (among "LR", "RF", "ET", "XGB", "LGB", "NN", "CB").
list of (lite) models to select with lite FE & default hyperparameters (among "LR", "RF", "ET", "XGB", "LGB", "NN", "CB", "NBC").
list of simple models to select (among "LR", "DT").
boolean, do we allow to include blend in the modelisation.
name of the weight columns.
list of feature engineering to select (among "Counter", "Date", "freq", "text_tfidf", "text_word2vec", "text_embedding", "tenc", "poly", "pca", "kmean").
number of features to keep after the feature selection process.
time budget in minutes of the feature selection process.
id of the dataset folder (images).
name of the file name path (images).
name of the column matching the lower y value of the image (object detection).
name of the column matching the higher y value of the image (object detection).
name of the column matching the lower x value of the image (object detection).
name of the column matching the higher x value of the image (object detection).
name of column containing the timestamp (time series).
value of the start of derivative window (time series), should be a strict negative integer.
value of the end of derivative window (time series), should be a negative integer greater than start_dw.
value of the start of forecast window (time series), should be a strict positive integer.
value of the end of forecast window (time series), should be a strict positive integer greater than start_fw.
list of name of feature that describes groups (time series).
list of name of feature that are a priori (time series).
content column name (text-similarity).
id of the dataset containing queries (text-similarity).
name of the column containing queries in the query dataset (text-similarity).
name of the ID column in the query dataset (text-similarity).
name of the column matching id in the description dataset (text-similarity).
top k individual to find (text-similarity).
lang of the text (text-similarity).
parameters of the model (text-similarity).
name of the external model (external model).
path to the onnx file (external model).
path to the yaml file (external model).
list - experiment information.