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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
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