Welcome
Developer Guide
Xplain
Explainability gives an explanation about Prediction and Model.

HCL MaxAI Workbench Documentation
System Requirements
Release Notes
Installation Guide
Developer Guide
- Overview
  To access the MaxAI Workbench REST API interface, use the following URL:
- 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.
- 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.
  - Xplaining Model
    xplain Model API gives the insights of input data and explain the details of its important features.
  - Xplaining Prediction
    Xplain Prediction API explains the details about prediction concerning its precision, confidence, reason, along with force plot and decision plot.
  - Xplaining Batch Prediction
- 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

Xplain

Explainability gives an explanation about Prediction and Model.

There are two types of API's in explainability:

Xplain Model
Xplain Prediction