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KetepatanAccuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures howR-kuasa dua yang diselaraskan (R²_adj)Adjusted R² is a corrected version of the coefficient of determination that accounts for the number of predictors in a regression model. Introduced by Henri Theil in 1961, it addreIndeks Rand TerlarasThe Adjusted Rand Index (ARI), developed by Hubert and Arabie in 1985, is an external clustering evaluation metric that measures the agreement between a predicted clustering and a Kriteria Maklumat Akaike (AIC)The Akaike Information Criterion is an information-theoretic measure for model selection that balances goodness of fit against model complexity. Introduced by Hirotugu Akaike in 19Akurasi SeimbangBalanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regarSkor BrierThe Brier score measures the mean squared difference between predicted probabilities and actual binary outcomes. It is a simple, interpretable metric for evaluating the accuracy of
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KetepatanR-kuasa dua yang diselaraskan (R²_adj)Indeks Rand TerlarasKriteria Maklumat Akaike (AIC)Akurasi SeimbangSkor BrierSoal Selidik Bentuk Badan (BSQ)Indeks Calinski-HarabaszPenentukur kalibrasi kalorimeterAnalisis Item Ujian Adaptif BerkomputerMatriks KebingunganPenjelasan KontrafaktualIndeks Davies-BouldinIndeks DunnKaedah SikuAturan Perkaitan Boleh JelasPengesanan Anomali Autoenkoder yang Boleh DijelaskanPohon Keputusan Boleh DijelasFP-Growth Boleh DijelaskanModel Campuran Gaussian Boleh JelasGaussian Process Boleh TerangkanHDBSCAN Boleh DijelaskanIsolation Forest Boleh DijelaskanK-Means Boleh TerangK-Nearest Neighbors Boleh DijelaskanExplainable LightGBMNaive Bayes Boleh DijelaskanSVM Satu Kelas Boleh JelasRandom Forest Boleh Dijelas (Explainable Random Forest)Tingkat Tumpukan yang Boleh DijelaskanMesin Vektor Sokongan Boleh DijelaskanEnsembel Undian yang Boleh DijelaskanXGBoost Boleh DijelaskanSkor F-betaSkor F1Pembelajaran Mesin Sedar KeadilanIndeks Fowlkes-MallowsGap StatisticMorfometrik GeometriKualiti Hidup Glaukoma-15Kerugian HammingInersiaIndeks JaccardCarta Angkat dan Carta UntungLIME: Penjelasan Model Boleh Ditafsir Secara Lokal dan Model-AgnostikLog-Loss (Silih Ganti Entropi)Analisis Item LongitudinalF1 makro-purataRalat Mutlak Min (MAE)Ralat Peratusan Mutlak Min (MAPE)Ralat Skala Purata Mutlak (MASE)Ralat Kuasa Dua Min (MSE)F1-skor min-purataPenyelarasan ModelMaklumat Bersaling UnggulKepersisanAUC Precision-RecallSkala Keadilan HargaR-squared (R²)Deria (Sensitiviti)Model Rasch RobustRalat Punca Min Kuasa Dua (RMSE)SHAP (SHapley Additive exPlanations)Model Rasch Bentuk PendekTeori Respons Item Bentuk Pendek (SF-IRT)Skor SiluetKetepatan (Specificity)Pembobotan dan Kalibrasi TinjauanMAPE Simetri (sMAPE)Algoritma Pengehadan Kadar Token BucketUkuran-VF1 PemberatStatistik J Youden