Overview Use Cases Customer Churn Prediction Time Series Anomaly Detection Event Anomaly Detection Cloud Spend Alerts Personalized Promotions Predictive Modeling Real-Time Forecasting Financial Metrics Forecasting Demand Forecasting Cumulative Forecasting Text extraction and classification NLP Powered Search Sentiment Analysis Finetuned LLM ChatLLM Language Detection Image Classification & Detection Object Detection Clustering Timeseries Clustering Sales and Revenue Forecasting Predictive Lead Scoring Personalized Search Personalized Recommendations Related Items Model Drift and Monitoring Feature Group Requirements Training Models Predictions Tensorflow with Vector Matching Custom Python Model Data Ingestion Streaming Feature Store Vector Store AI Agents Named Entity Recognition Guidelines Optimization Connectors Authentication Getting Started with the Python SDK API Reference API Classes API Inputs Documentation Chat Bot API Search Video Tutorials ChatLLM

Required Feature Group Types

To train a model under this use case, you will need to create feature groups of the following type(s):

Feature Group Type	API Configuration Name	Required	Description
Training Data Table	TRAINING_DATA	True	Dataset representing the distribution of features encountered by a model during training.
Prediction Log Table	PREDICTION_LOG	True	Dataset representing the distribution of features encountered by a model during prediction or deployment.

Note: Once you upload the datasets under each Feature Group Type that comply with their respective required schemas, you will need to create Machine learning (ML) features that would be used to train your ML model(s). We use the term, "Feature Group" for a group of ML features (dataset columns) under a specific Feature Group Type. Our system support extensible schemas that enables you to provide any number of additional columns/features that you think are relevant to that Feature Group Type.

Feature Group: Training Data Table

Dataset representing the distribution of features encountered by a model during training.

Feature Mapping	Feature Type	Required	Description
TARGET		Y	The target value the model is training to predict
MODEL_VERSION	categorical	N	The unique identifier of the model version that was trained with this training row.
PREDICTED_VALUE		N	Model output value for this prediction data.
IMAGE	objectreference	N	Image reference
DOCUMENT		N	Document text

Feature Group: Prediction Log Table

Dataset representing the distribution of features encountered by a model during prediction or deployment.

Feature Mapping	Feature Type	Required	Description
PREDICTION_TIME	timestamp	N	Timestamp of the prediction.
ACTUAL		N	The ground truth value of this prediction data.
PREDICTED_VALUE		N	Model output value for this prediction data.
PREDICTED_PROBABILITY		N	Model output probability value for prediction data.
MODEL_VERSION	categorical	N	The unique identifier of the model version corresponding to the prediction.
PROTECTED_CLASS	categorical	N	Protected class to compute model bias metrics on.
IMAGE	objectreference	N	Image reference
DOCUMENT		N	Document text