Welcome
Developer Guide
Prediction
The Prediction section lists APIs that are used for handling single prediction and batch prediction.
Handling Batch Prediction
The handle_batch_prediction API endpoint is designed for batch predictions, allowing users to predict outcomes for a set of input data. It provides options to either view/download the prediction results. The prediction process is carried out by calling a function from prediction_package.batch_prediction_helper.

Release Notes
Installation Guide
Developer Guide
- Overview
  To access the Marketing AION REST API interface, use the Docker Desktop application to start the Docker container.
- Tracker
- API Status
  Use these APIs to get the status and set the status of the different types of API.
- Data Handler Overview
  Data Handler has four different APIs, and three of the APIs represent a different method uploading data.
- Training
  For Training, you can execute either of the generic training by using Train for pipeline API.
- Prediction
  The Prediction section lists APIs that are used for handling single prediction and batch prediction.
  - Handling Single Prediction
    The handle_single_prediction API is designed to handle single predictions by sending a POST request to a prediction endpoint. It takes input data containing the usecase ID, version, and data for prediction. The prediction is made by asynchronously posting the data to the specified prediction endpoint.
  - Handling Batch Prediction
    The handle_batch_prediction API endpoint is designed for batch predictions, allowing users to predict outcomes for a set of input data. It provides options to either view/download the prediction results. The prediction process is carried out by calling a function from prediction_package.batch_prediction_helper.
- Model Inference (beta)
- Download-model
  These APIs are used to download Python package, Docker container package, and Mlac.
- Monitoring
  Monitoring ML models checks for changes in data distribution ensuring that data is maintaining an acceptable level of variation.
- Xplain
  Explainability gives an explanation about Prediction and Model.
- Usecases
  Use the following APIs to retrieve the Use Case list, to delete use cases, and to retrieve the logs.
- EDA
- AutoPilot
  This Autopilot Mode refers to a feature that allows users to build an automated model without direct human intervention.
- Data Generator
- Building Usecases with API
  To build a usecase or to train a model, complete the following steps:
MLAC User Guide
User Guide

Handling Batch Prediction

The handle_batch_prediction API endpoint is designed for batch predictions, allowing users to predict outcomes for a set of input data. It provides options to either view/download the prediction results. The prediction process is carried out by calling a function from prediction_package.batch_prediction_helper.

Method

GET

Endpoint

/v1/aion/problemtype/prediction/batchprediction/

Request Parameters


outputOption	Mandatory
path_type	Mandatory
tracking_id	Mandatory	Tracking ID for the batch prediction.
usecaseid	Mandatory	The ID of the use case for which you want the prediction results.
model_version	Mandatory	The version number of the model.
predict_file_path		The path where the prediction results are to be stored.

After providing the values, click Execute.

Response Parameters

After clicking Execute, you get a Response similar to the following example:

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