Metrics Node Catalog

Metrics category

Generated from 5 catalog nodes in AI/ML/Metrics.

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Showing 5 of 5 generated node docs.

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A

Accuracy

AI/ML/Metrics

Calculate classification accuracy by comparing predictions to actual values

4 in2 outSecurity 8/10

C

Confusion Matrix

AI/ML/Metrics

Build confusion matrix and calculate precision, recall, and F1 score

4 in2 outSecurity 8/10

R

ROC-AUC & Log Loss

AI/ML/Metrics

Threshold-free evaluation of a binary classifier: area under the ROC curve, log loss and the curve points. This is the payoff for Logistic Regression producing calibrated probabilities instead of bare class labels.

5 in4 outSecurity 8/10

R

Regression Metrics

AI/ML/Metrics

Calculate MSE, RMSE, MAE, and R² for regression predictions

4 in2 outSecurity 8/10

S

Silhouette Score

AI/ML/Metrics

Evaluate clustering quality: how much closer each sample sits to its own cluster than to the nearest other one (-1 to +1)

5 in4 outSecurity 8/10