Check if experiment exists, verifies parameters, creates data to create_experiment function and finally starts creation of MLJAR experiment.
add_experiment_if_not_exists(project_hid, train_dataset, valid_dataset,
experiment_title, project_task, validation_kfolds, validation_shuffle,
validation_stratify, validation_train_split, algorithms, metric, tuning_mode,
time_constraint, create_ensemble)character with project identifier
character with path to training dataset
character with path to validation dataset
character with experiment title
character with project task
number of folds to be used in validation
boolean which specify if shuffle samples before training
boolean which decides whether samples will be divided into folds with the same class distribution
ratio how to split training dataset into train and validation
list of algorithms to use
charcater with metric
tuning mode
numeric with time limit to calculate algorithm
whether or not to create ensemble
experiment details structure