Matrix : Predict L1 L2 L3 Actual L1 3 0 2 L2 0 1 1 L3 0 2 3 Normalized Matrix : Predict L1 L2 L3 Actual L1 0.6 0.0 0.4 L2 0.0 0.5 0.5 L3 0.0 0.4 0.6 Overall Statistics : 95% CI (0.30439,0.86228) ACC Macro 0.72222 ARI 0.09206 AUNP 0.68571 AUNU 0.67857 Bangdiwala B 0.37255 Bennett S 0.375 CBA 0.47778 CSI 0.17778 Chi-Squared 6.6 Chi-Squared DF 4 Conditional Entropy 0.97579 Cramer V 0.5244 Cross Entropy 1.58333 F1 Macro 0.56515 F1 Micro 0.58333 FNR Macro 0.43333 FNR Micro 0.41667 FPR Macro 0.20952 FPR Micro 0.20833 Gwet AC1 0.38931 Hamming Loss 0.41667 Joint Entropy 2.45915 KL Divergence 0.09998 Kappa 0.35484 Kappa 95% CI (-0.07708,0.78675) Kappa No Prevalence 0.16667 Kappa Standard Error 0.22036 Kappa Unbiased 0.34426 Krippendorff Alpha 0.37158 Lambda A 0.42857 Lambda B 0.16667 Mutual Information 0.52421 NIR 0.41667 NPV Macro 0.77778 NPV Micro 0.79167 Overall ACC 0.58333 Overall CEN 0.46381 Overall J (1.225,0.40833) Overall MCC 0.36667 Overall MCEN 0.51894 Overall RACC 0.35417 Overall RACCU 0.36458 P-Value 0.18926 PPV Macro 0.61111 PPV Micro 0.58333 Pearson C 0.59568 Phi-Squared 0.55 RCI 0.35339 RR 4.0 Reference Entropy 1.48336 Response Entropy 1.5 SOA1(Landis & Koch) Fair SOA2(Fleiss) Poor SOA3(Altman) Fair SOA4(Cicchetti) Poor SOA5(Cramer) Relatively Strong SOA6(Matthews) Weak SOA7(Lambda A) Moderate SOA8(Lambda B) Very Weak SOA9(Krippendorff Alpha) Low SOA10(Pearson C) Strong Scott PI 0.34426 Standard Error 0.14232 TNR Macro 0.79048 TNR Micro 0.79167 TPR Macro 0.56667 TPR Micro 0.58333 Zero-one Loss 5 Class Statistics : Classes L1 L2 L3 ACC(Accuracy) 0.83333 0.75 0.58333 AGF(Adjusted F-score) 0.72859 0.62869 0.61009 AGM(Adjusted geometric mean) 0.85764 0.70861 0.58034 AM(Difference between automatic and manual classification) -2 1 1 AUC(Area under the ROC curve) 0.8 0.65 0.58571 AUCI(AUC value interpretation) Very Good Fair Poor AUPR(Area under the PR curve) 0.8 0.41667 0.55 BB(Braun-Blanquet similarity) 0.6 0.33333 0.5 BCD(Bray-Curtis dissimilarity) 0.08333 0.04167 0.04167 BM(Informedness or bookmaker informedness) 0.6 0.3 0.17143 CEN(Confusion entropy) 0.25 0.49658 0.60442 DOR(Diagnostic odds ratio) None 4.0 2.0 DP(Discriminant power) None 0.33193 0.16597 DPI(Discriminant power interpretation) None Poor Poor ERR(Error rate) 0.16667 0.25 0.41667 F0.5(F0.5 score) 0.88235 0.35714 0.51724 F1(F1 score - harmonic mean of precision and sensitivity) 0.75 0.4 0.54545 F2(F2 score) 0.65217 0.45455 0.57692 FDR(False discovery rate) 0.0 0.66667 0.5 FN(False negative/miss/type 2 error) 2 1 2 FNR(Miss rate or false negative rate) 0.4 0.5 0.4 FOR(False omission rate) 0.22222 0.11111 0.33333 FP(False positive/type 1 error/false alarm) 0 2 3 FPR(Fall-out or false positive rate) 0.0 0.2 0.42857 G(G-measure geometric mean of precision and sensitivity) 0.7746 0.40825 0.54772 GI(Gini index) 0.6 0.3 0.17143 GM(G-mean geometric mean of specificity and sensitivity) 0.7746 0.63246 0.58554 HD(Hamming distance) 2 3 5 IBA(Index of balanced accuracy) 0.36 0.28 0.35265 ICSI(Individual classification success index) 0.6 -0.16667 0.1 IS(Information score) 1.26303 1.0 0.26303 J(Jaccard index) 0.6 0.25 0.375 LS(Lift score) 2.4 2.0 1.2 MCC(Matthews correlation coefficient) 0.68313 0.2582 0.16903 MCCI(Matthews correlation coefficient interpretation) Moderate Negligible Negligible MCEN(Modified confusion entropy) 0.26439 0.5 0.6875 MK(Markedness) 0.77778 0.22222 0.16667 N(Condition negative) 7 10 7 NLR(Negative likelihood ratio) 0.4 0.625 0.7 NLRI(Negative likelihood ratio interpretation) Poor Negligible Negligible NPV(Negative predictive value) 0.77778 0.88889 0.66667 OC(Overlap coefficient) 1.0 0.5 0.6 OOC(Otsuka-Ochiai coefficient) 0.7746 0.40825 0.54772 OP(Optimized precision) 0.58333 0.51923 0.55894 P(Condition positive or support) 5 2 5 PLR(Positive likelihood ratio) None 2.5 1.4 PLRI(Positive likelihood ratio interpretation) None Poor Poor POP(Population) 12 12 12 PPV(Precision or positive predictive value) 1.0 0.33333 0.5 PRE(Prevalence) 0.41667 0.16667 0.41667 Q(Yule Q - coefficient of colligation) None 0.6 0.33333 QI(Yule Q interpretation) None Moderate Weak RACC(Random accuracy) 0.10417 0.04167 0.20833 RACCU(Random accuracy unbiased) 0.11111 0.0434 0.21007 TN(True negative/correct rejection) 7 8 4 TNR(Specificity or true negative rate) 1.0 0.8 0.57143 TON(Test outcome negative) 9 9 6 TOP(Test outcome positive) 3 3 6 TP(True positive/hit) 3 1 3 TPR(Sensitivity, recall, hit rate, or true positive rate) 0.6 0.5 0.6 Y(Youden index) 0.6 0.3 0.17143 dInd(Distance index) 0.4 0.53852 0.58624 sInd(Similarity index) 0.71716 0.61921 0.58547 One-Vs-All : L1-Vs-All : Predict L1 ~ Actual L1 3 2 ~ 0 7 L2-Vs-All : Predict L2 ~ Actual L2 1 1 ~ 2 8 L3-Vs-All : Predict L3 ~ Actual L3 3 2 ~ 3 4