[BETA] Compute the optimal prediction for each rows in a data frame, for a given model, a list of actionable features and a number of samples for each features to be tested.
helper_optimal_prediction(
project_id,
experiment_id,
model_id,
df,
actionable_features,
nb_sample,
maximize,
zip = FALSE,
version = 1
)id of the project containing the use case.
id of the experiment to be predicted on.
id of the model to be predicted on.
a data frame to be predicted on.
a list of actionable_featuress features contained in the names of the data frame.
a vector of number of sample for each actionable_features features.
a boolean indicating if we maximize or minimize the predicted target.
a boolean indicating if the data frame to predict should be zipped prior sending to the instance.
version of the use case we want to make the prediction on.
data.frame - optimal vector and the prediction associated with for each rows in the original data frame.