PyCM Report

Confusion Matrix :

Actual Predict
0 1 2
0 13 0 0
1 0 10 6
2 0 0 9

Overall Statistics :

95% CI (0.72617,0.95804)
Bennett_S 0.76316
Chi-Squared 52.25
Chi-Squared DF 4
Conditional Entropy 0.40187
Cramer_V 0.82916
Cross Entropy 1.65796
Gwet_AC1 0.76324
Hamming Loss 0.15789
Joint Entropy 1.94887
KL Divergence 0.11096
Kappa 0.76735
Kappa 95% CI (0.59651,0.93818)
Kappa No Prevalence 0.68421
Kappa Standard Error 0.08716
Kappa Unbiased 0.76299
Lambda A 0.72727
Lambda B 0.73913
Mutual Information 1.16374
NIR 0.42105
Overall_ACC 0.84211
Overall_CEN 0.16245
Overall_J (2.225,0.74167)
Overall_MCEN 0.18661
Overall_RACC 0.32133
Overall_RACCU 0.3338
P-Value 0.0
PPV_Macro 0.86667
PPV_Micro 0.84211
Phi-Squared 1.375
Reference Entropy 1.54701
Response Entropy 1.5656
Scott_PI 0.76299
Standard Error 0.05915
Strength_Of_Agreement(Altman) Good
Strength_Of_Agreement(Cicchetti) Excellent
Strength_Of_Agreement(Fleiss) Excellent
Strength_Of_Agreement(Landis and Koch) Substantial
TPR_Macro 0.875
TPR_Micro 0.84211
Zero-one Loss 6

Class Statistics :

Class 0 1 2 Description
ACC 1.0 0.84211 0.84211 Accuracy
BM 1.0 0.625 0.7931 Informedness or bookmaker informedness
CEN 0 0.24409 0.25 Confusion entropy
DOR None None None Diagnostic odds ratio
ERR 0.0 0.15789 0.15789 Error rate
F0.5 1.0 0.89286 0.65217 F0.5 score
F1 1.0 0.76923 0.75 F1 score - harmonic mean of precision and sensitivity
F2 1.0 0.67568 0.88235 F2 score
FDR 0.0 0.0 0.4 False discovery rate
FN 0 6 0 False negative/miss/type 2 error
FNR 0.0 0.375 0.0 Miss rate or false negative rate
FOR 0.0 0.21429 0.0 False omission rate
FP 0 0 6 False positive/type 1 error/false alarm
FPR 0.0 0.0 0.2069 Fall-out or false positive rate
G 1.0 0.79057 0.7746 G-measure geometric mean of precision and sensitivity
IS 1.54749 1.24793 1.34104 Information score
J 1.0 0.625 0.6 Jaccard index
LR+ None None 4.83333 Positive likelihood ratio
LR- 0.0 0.375 0.0 Negative likelihood ratio
MCC 1.0 0.70076 0.68983 Matthews correlation coefficient
MCEN 0 0.26532 0.26439 Modified confusion entropy
MK 1.0 0.78571 0.6 Markedness
N 25 22 29 Condition negative
NPV 1.0 0.78571 1.0 Negative predictive value
P 13 16 9 Condition positive or support
POP 38 38 38 Population
PPV 1.0 1.0 0.6 Precision or positive predictive value
PRE 0.34211 0.42105 0.23684 Prevalence
RACC 0.11704 0.1108 0.09349 Random accuracy
RACCU 0.11704 0.11704 0.09972 Random accuracy unbiased
TN 25 22 23 True negative/correct rejection
TNR 1.0 1.0 0.7931 Specificity or true negative rate
TON 25 28 23 Test outcome negative
TOP 13 10 15 Test outcome positive
TP 13 10 9 True positive/hit
TPR 1.0 0.625 1.0 Sensitivity, recall, hit rate, or true positive rate

Generated By PyCM Version 1.3