Welcome
Developer Guide
EDA
Fairness Metrics
Use this API to view the fairness metrics.

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.
- 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
  - Setting Data Location
    Use this API to set the location of the data being used by the EDA.
  - Records
    Use this API to view the records.
  - Data Overview
    Use this API to check the data overview.
  - Correlation Analysis
    Use this API for correlation analysis.
  - Unsupervised Clustering
    Use this API to view the unsupervised clustering.
  - Data Distribution
    Use this API to view the Data Distribution.
  - Feature Importance
    Use this API to check feature importance.
  - Pair Graph
    Use this API to view the pair graph.
  - Fairness Metrics
    Use this API to view the fairness metrics.
  - Timeseries Analysis
    Use this API to view the timeseries analysis.
- 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

Fairness Metrics

Use this API to view the fairness metrics.

Method

POST

Endpoint

/v1/aion/problemtype/eda/fairness_metrics

Request Parameters


feature_col1	Mandatory	The feature to check bias for.
feature_col2	Mandatory	The target feature.
graphType	Mandatory	Valid values are: `Statistical Parity Difference` `Disparate Impact` `Theil Index`

Click Execute.

Response Parameters

After clicking Execute, you get the following response:

Download_file

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