Skip to content
Scholar
Gate
Search the library…
⌘K
Library
Bookshelf
Desk
Review Studio
Assistant
EN
Sign in
Home
/
Model Evaluation
Model Evaluation
41 methods.
Classification Metric
13
Accuracy
Balanced Accuracy
F-beta Score
F1-Score
Macro-averaged F1
Matthews Correlation Coefficient
Micro-averaged F1
Precision
Precision-Recall AUC
Recall (Sensitivity)
Specificity
Weighted F1
Youdens J Statistic
External Clustering Validation
4
Adjusted Rand Index
Fowlkes-Mallows Index
Normalized Mutual Information
V-measure
Clustering Validation
4
Calinski-Harabasz Index
Davies-Bouldin Index
Dunn Index
Silhouette Score
Error metric
3
Mean Absolute Error
Mean Squared Error
Root Mean Squared Error
Regression evaluation
2
Adjusted R-squared
R-squared
Information-theoretic criterion
2
Akaike Information Criterion
Bayesian Information Criterion
Probabilistic Loss Metric
2
Brier Score
Log-Loss (Cross-Entropy Loss)
Cluster Number Selection
2
Elbow Method
Gap Statistic
Multi-label Metric
2
Hamming Loss
Jaccard Index
Relative error metric
2
Mean Absolute Percentage Error
Symmetric MAPE
Diagnostic Tool
1
Confusion Matrix
Statistical testing
1
Goodness-of-Fit
Cluster Cohesion Measure
1
Inertia (Within-Cluster Sum of Squares)
Classification Evaluation Tool
1
Lift and Gain Chart
Scaled error metric
1
Mean Absolute Scaled Error
ScholarGate