Evaluasi Model

41 metode.

Classification Metric 13

Akurasi Akurasi Seimbang Skor F-beta Skor-F1 F1 Makro Koefisien Korelasi Matthews F1-mikro Presisi AUC Presisi-Recall Recall (Sensitivitas)Spesifisitas F1-tertimbang Statistik J Youden

External Clustering Validation 4

Indeks Rand yang Disesuaikan Indeks Fowlkes-Mallows Informasi Bersama Ternormalisasi V-measure

Clustering Validation 4

Indeks Calinski-Harabasz Indeks Davies-Bouldin Indeks Dunn Silhouette Score

Error metric 3

Rata-rata Kesalahan Absolut (MAE)Mean Squared Error (MSE)Root Mean Squared Error (RMSE)

Regression evaluation 2

R-squared yang Disesuaikan (R²_adj)R-squared

Information-theoretic criterion 2

Kriteria Informasi Akaike (AIC)Kriteria Informasi Bayesian (BIC)

Probabilistic Loss Metric 2

Skor Brier Log-Loss (Cross-Entropy Loss)

Cluster Number Selection 2

Metode Siku Statistik Gap

Multi-label Metric 2

Kerugian Hamming Indeks Jaccard

Relative error metric 2

Kesalahan Persentase Absolut Rata-rata (MAPE)MAPE Simetris (sMAPE)

Diagnostic Tool 1

Matriks Kebingungan

Statistical testing 1

Pengujian Kecocokan (Goodness-of-Fit)

Cluster Cohesion Measure 1

Classification Evaluation Tool 1

Grafik Lift dan Gain

Scaled error metric 1

Mean Absolute Scaled Error (MASE)