Model Evaluation Functions - Teradata Vantage

Teradata® VantageCloud Lake

Deployment

VantageCloud

Edition

Lake

Product

Teradata Vantage

Published

January 2023

Language

English (United States)

Last Update

2024-04-03

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TD_Silhouette: Determines how well the data is clustered among clusters.
TD_ClassificationEvaluator: Computes the Confusion matrix, precision, recall, and F1-score based on the observed labels (true labels) and the predicted labels.
TD_RegressionEvaluator: Computes metrics to evaluate and compare multiple models and summarizes how close predictions are to their expected values.
TD_ROC: Accepts a set of prediction-actual pairs for a binary classification model and calculates the True-positive rate (TPR), False-positive rate (FPR), The area under the ROC curve (AUC), and Gini coefficient values for a range of discrimination thresholds.
TD_TrainTestSplit: Simulates model performance on new data.
TD_DecisionForestPredict: Uses the model output by TD_DecisionForest function to analyze the input data and make predictions.