PyCM Report

Confusion Matrix :

Actual Predict
0 1 2
0 13 0 0
1 0 15 1
2 0 3 6

Overall Statistics :

95% CI (0.79716,0.99231)
Bennett_S 0.84211
Chi-Squared 53.85218
Chi-Squared DF 4
Conditional Entropy 0.35951
Cramer_V 0.84177
Cross Entropy 1.56133
Gwet_AC1 0.84537
Joint Entropy 1.90651
KL Divergence 0.01432
Kappa 0.8355
Kappa 95% CI (0.68301,0.98799)
Kappa No Prevalence 0.78947
Kappa Standard Error 0.0778
Kappa Unbiased 0.83514
Lambda A 0.81818
Lambda B 0.8
Mutual Information 1.13011
Overall_ACC 0.89474
Overall_J (2.38947,0.79649)
Overall_RACC 0.36011
Overall_RACCU 0.3615
PPV_Macro 0.89683
PPV_Micro 0.89474
Phi-Squared 1.41716
Reference Entropy 1.54701
Response Entropy 1.48962
Scott_PI 0.83514
Standard Error 0.04978
Strength_Of_Agreement(Altman) Very Good
Strength_Of_Agreement(Cicchetti) Excellent
Strength_Of_Agreement(Fleiss) Excellent
Strength_Of_Agreement(Landis and Koch) Almost Perfect
TPR_Macro 0.86806
TPR_Micro 0.89474

Class Statistics :

Class 0 1 2 Description
ACC 1.0 0.89474 0.89474 Accuracy
BM 1.0 0.80114 0.63218 Informedness or bookmaker informedness
DOR None 95.0 56.0 Diagnostic odds ratio
ERR 0.0 0.10526 0.10526 Error rate
F0.5 1.0 0.85227 0.81081 F0.5 score
F1 1.0 0.88235 0.75 F1 score - harmonic mean of precision and sensitivity
F2 1.0 0.91463 0.69767 F2 score
FDR 0.0 0.16667 0.14286 False discovery rate
FN 0 1 3 False negative/miss/type 2 error
FNR 0.0 0.0625 0.33333 Miss rate or false negative rate
FOR 0.0 0.05 0.09677 False omission rate
FP 0 3 1 False positive/type 1 error/false alarm
FPR 0.0 0.13636 0.03448 Fall-out or false positive rate
G 1.0 0.88388 0.75593 G-measure geometric mean of precision and sensitivity
J 1.0 0.78947 0.6 Jaccard index
LR+ None 6.875 19.33333 Positive likelihood ratio
LR- 0.0 0.07237 0.34524 Negative likelihood ratio
MCC 1.0 0.79218 0.69332 Matthews correlation coefficient
MK 1.0 0.78333 0.76037 Markedness
N 25 22 29 Condition negative
NPV 1.0 0.95 0.90323 Negative predictive value
P 13 16 9 Condition positive
POP 38 38 38 Population
PPV 1.0 0.83333 0.85714 Precision or positive predictive value
PRE 0.34211 0.42105 0.23684 Prevalence
RACC 0.11704 0.19945 0.04363 Random accuracy
RACCU 0.11704 0.20014 0.04432 Random accuracy unbiased
TN 25 19 28 True negative/correct rejection
TNR 1.0 0.86364 0.96552 Specificity or true negative rate
TON 25 20 31 Test outcome negative
TOP 13 18 7 Test outcome positive
TP 13 15 6 True positive/hit
TPR 1.0 0.9375 0.66667 Sensitivity, recall, hit rate, or true positive rate

Generated By PyCM Version 0.9.5