predictive

relationalai.semantics.reasoners

RelationalAI Predictive Reasoner using Graph Neural Networks (GNNs).

The Predictive Reasoner generates meaningful predictions from your relational data, supporting decision-intelligence tasks like identifying potential churn, detecting fraud, and more.

It provides a declarative Python API for formulating prediction problems — node classification, regression, or link prediction — and solving them with Graph Neural Networks.

Classes

Classes exposed by this module.

GNN Train, load, register and predict with a Graph Neural Network. Re-exported from relationalai.semantics.reasoners.predictive.estimator.

PropertyTransformer Annotate concept fields with semantic types for GNN data preparation. Re-exported from relationalai.semantics.reasoners.predictive.property_transformer.

Modules and Subpackages

Submodules and subpackages available under this namespace.

estimator GNN estimator for training, loading, registering and predicting with Graph Neural Networks.

property_transformer Semantic type annotations for GNN feature columns.

Referenced By

RelationalAI Documentation
└──  Release Notes
    └──  Python API Release Notes
        └──  What’s New in Version 1.4.1
            └──  New Features and Enhancements