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| create_connector | Create a new connector of a supported type (among: "SQL", "FTP", "SFTP", "S3", "GCP"). If check_if_exist is enabled, the function will check if a connector with the same name already exists. If yes, it will return a message and the information of the existing connector instead of creating a new one. |
| create_dataframe_from_dataset | Create a dataframe from a dataset_id. |
| create_dataset_embedding | Create a dataset embedding from a dataset_id. |
| create_dataset_from_dataframe | Upload dataset from data frame. |
| create_dataset_from_datasource | Create a dataset from an existing datasource. |
| create_dataset_from_file | Upload dataset from file name. |
| create_datasource | Create a new datasource If check_if_exist is enabled, the function will check if a datasource with the same name already exists. If yes, it will return a message and the information of the existing datasource instead of creating a new one. |
| create_deployment_api_key | Create a new API key for a deployed model. |
| create_deployment_model | Create a new deployment for a model. |
| create_deployment_predictions | Create predictions on a deployed model using a dataset. |
| create_experiment | Create a new experiment. If check_if_exist is enabled, the function will check if an experiment with the same name already exists. If yes, it will return a message and the information of the existing experiment instead of creating a new one. |
| create_experiment_version | Create a new version of an existing experiment. |
| create_export | Export data using an existing exporter and the resource to export |
| create_exporter | Create a new exporter |
| create_folder | Upload folder from a local file. |
| create_pipeline_trigger | Trigger an existing pipeline run. |
| create_prediction | Create a prediction on a specified experiment_version |
| create_project | Create a new project. If check_if_exist is enabled, the function will check if a project with the same name already exists. If yes, it will return a message and the information of the existing project instead of creating a new one. |
| create_project_user | Add user in and existing project. |
| delete_connector | Delete an existing connector. |
| delete_dataset | Delete an existing dataset. |
| delete_datasource | Delete a datasource |
| delete_deployment | Delete an existing deployment. |
| delete_experiment | Delete a experiment on the platform. |
| delete_exporter | Delete an exporter |
| delete_folder | Delete an existing folder. |
| delete_pipeline | Delete an existing pipeline |
| delete_prediction | Delete a prediction. |
| delete_project | Delete an existing project. |
| delete_project_user | Delete user in and existing project. |
| get_best_model_id | Get the model_id that provide the best predictive performance given experiment_version_id. If include_blend is false, it will return the model_id from the best "non blended" model. |
| get_connectors | Get information of all connectors available for a given project_id. |
| get_connector_id_from_name | Get a connector_id from a connector_name for a given project_id. If duplicated name, the first connector_id that match it is retrieved. |
| get_connector_info | Get information about connector from its id. |
| get_datasets | Get information of all datasets available for a given project_id. |
| get_dataset_embedding | Get a dataset embedding from a dataset_id. |
| get_dataset_head | Show the head of a dataset from its id. |
| get_dataset_id_from_name | Get a dataset_id from a dataset_name. If duplicated name, the first dataset_id that match it is retrieved. |
| get_dataset_info | Get a dataset from its id. |
| get_datasources | Get information of all data sources available for a given project_id. |
| get_datasource_id_from_name | Get a datasource_id from a datasource_name If duplicated name, the first datasource_id that match it is retrieved |
| get_datasource_info | Get a datasource from its id. |
| get_deployments | Get information of all deployments of a given type available for a given project_id. |
| get_deployment_api_keys | Get API keys for a deployed model. |
| get_deployment_app_logs | Get logs from a deployed app. |
| get_deployment_id_from_name | Get a deployment_id from a name and type for a given project_id. If duplicated name, the first deployment_id that match it is retrieved. |
| get_deployment_info | Get information about a deployment from its id. |
| get_deployment_predictions | Get listing of predictions related to a deployment_id. |
| get_deployment_prediction_info | Get information related to predictions of a prediction_id. |
| get_deployment_usage | Get usage (calls, errors and response time) of the last version of a deployed model. |
| get_experiments | Get information of all experiments available for a given project_id. |
| get_experiment_id_from_name | Get a experiment_id from a experiment_name If duplicated name, the first experiment_id that match it is retrieved. |
| get_experiment_info | Get a experiment from its experiment_id. |
| get_experiment_version_features | Get features information related to a experiment_version_id. |
| get_experiment_version_id | Get a experiment version id from a experiment_id and its version number. |
| get_experiment_version_info | Get a experiment_version info from its experiment_version_id |
| get_experiment_version_models | Get a model list related to a experiment_version_id. |
| get_experiment_version_predictions | Get a list of prediction from a experiment_version_id. |
| get_exporters | Get information of all exporters available for a given project_id. |
| get_exporter_exports | Get all exports done from an exporter_id |
| get_exporter_id_from_name | Get a exporter_id from a exporter_name. If duplicated name, the first exporter_id that match it is retrieved |
| get_exporter_info | Get an exporter from its id. |
| get_features_infos | Get information of a given feature related to a experiment_version_id. |
| get_folder | Get a folder from its id. |
| get_folders | Get information of all image folders available for a given project_id. |
| get_folder_id_from_name | Get a folder_id from a folder_name. If duplicated name, the first folder_id that match it is retrieved. |
| get_model_cv | Get the cross validation file from a specific model. |
| get_model_feature_importance | Get feature importance corresponding to a model_id. |
| get_model_hyperparameters | Get hyperparameters corresponding to a model_id. |
| get_model_infos | Get model information corresponding to a model_id. |
| get_pipelines | Get information of all pipelines of a given type available for a given project_id. |
| get_pipeline_id_from_name | Get a pipeline_id from a pipeline_name and type for a given project_id. If duplicated name, the first pipeline_id that match it is retrieved. |
| get_pipeline_info | Get information about a pipeline from its id and its type. |
| get_prediction | Get a specific prediction from a prediction_id. Wait up until time_out is reached and wait wait_time between each retry. |
| get_prediction_infos | Get a information about a prediction_id. |
| get_projects | Retrieves all projects. |
| get_project_id_from_name | Get a project_id from a project_name If duplicated name, the first project_id that match it is retrieved. |
| get_project_info | Get a project from its project_id. |
| get_project_users | Get users from a project. |
| helper_cv_classif_analysis | Get metrics on a CV file retrieved by Prevision.io for a binary classification use case |
| helper_drift_analysis | [BETA] Return a data.frame that contains features, a boolean indicating if the feature may have a different distribution between the submitted datasets (if p-value < threshold), their exact p-value and the test used to compute it. |
| helper_optimal_prediction | [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_plot_classif_analysis | Plot RECALL, PRECISION & F1 SCORE versus top n predictions for a binary classification use case |
| pause_experiment_version | Pause a running experiment_version on the platform. |
| pio_download | Download resources according specific parameters. |
| pio_init | Initialization of the connection to your instance Prevision.io. |
| pio_list_to_df | Convert a list returned from APIs to a dataframe. Only working for consistent list (same naming and number of columns). |
| pio_request | Request the platform. Thanks to an endpoint, the url and the API, you can create request. |
| resume_experiment_version | Resume a paused experiment_version on the platform. |
| stop_experiment_version | Stop a running or paused experiment_version on the platform. |
| test_connector | Test an existing connector. |
| test_datasource | Test a datasource |
| test_deployment_type | Check if a type of a deployment is supported |
| test_pipeline_type | Check if a type of a pipeline is supported |
| update_experiment_version_description | Update the description of a given experiment_version_id. |
| update_project_user_role | Update user role in and existing project. |