def __overall_stat_init__(cm):
    """
    Init individual overall stat.

    :param cm: ConfusionMatrix
    :type cm : pycm.ConfusionMatrix object
    :return: None
    """
    cm.Overall_J = cm.overall_stat['Overall J']
    cm.SOA1 = cm.overall_stat['SOA1(Landis & Koch)']
    cm.SOA2 = cm.overall_stat['SOA2(Fleiss)']
    cm.SOA3 = cm.overall_stat['SOA3(Altman)']
    cm.SOA4 = cm.overall_stat['SOA4(Cicchetti)']
    cm.Kappa = cm.overall_stat['Kappa']
    cm.Overall_ACC = cm.overall_stat['Overall ACC']
    cm.TNR_Macro = cm.overall_stat['TNR Macro']
    cm.TPR_Macro = cm.overall_stat['TPR Macro']
    cm.FNR_Macro = cm.overall_stat['FNR Macro']
    cm.FPR_Macro = cm.overall_stat['FPR Macro']
    cm.PPV_Macro = cm.overall_stat['PPV Macro']
    cm.ACC_Macro = cm.overall_stat['ACC Macro']
    cm.TNR_Micro = cm.overall_stat['TNR Micro']
    cm.FPR_Micro = cm.overall_stat['FPR Micro']
    cm.TPR_Micro = cm.overall_stat['TPR Micro']
    cm.FNR_Micro = cm.overall_stat['FNR Micro']
    cm.PPV_Micro = cm.overall_stat['PPV Micro']
    cm.F1_Macro = cm.overall_stat['F1 Macro']
    cm.F1_Micro = cm.overall_stat['F1 Micro']
    cm.Overall_RACC = cm.overall_stat['Overall RACC']
    cm.Overall_RACCU = cm.overall_stat['Overall RACCU']
    cm.PI = cm.overall_stat['Scott PI']
    cm.AC1 = cm.overall_stat['Gwet AC1']
    cm.S = cm.overall_stat['Bennett S']
    cm.Kappa_SE = cm.overall_stat['Kappa Standard Error']
    cm.Kappa_CI = cm.overall_stat['Kappa 95% CI']
    cm.Chi_Squared = cm.overall_stat['Chi-Squared']
    cm.Phi_Squared = cm.overall_stat['Phi-Squared']
    cm.KappaUnbiased = cm.overall_stat['Kappa Unbiased']
    cm.KappaNoPrevalence = cm.overall_stat['Kappa No Prevalence']
    cm.V = cm.overall_stat['Cramer V']
    cm.DF = cm.overall_stat['Chi-Squared DF']
    cm.CI95 = cm.overall_stat['95% CI']
    cm.SE = cm.overall_stat['Standard Error']
    cm.ReferenceEntropy = cm.overall_stat['Reference Entropy']
    cm.ResponseEntropy = cm.overall_stat['Response Entropy']
    cm.CrossEntropy = cm.overall_stat['Cross Entropy']
    cm.JointEntropy = cm.overall_stat['Joint Entropy']
    cm.ConditionalEntropy = cm.overall_stat['Conditional Entropy']
    cm.MutualInformation = cm.overall_stat['Mutual Information']
    cm.KL = cm.overall_stat['KL Divergence']
    cm.LambdaB = cm.overall_stat['Lambda B']
    cm.LambdaA = cm.overall_stat['Lambda A']
    cm.HammingLoss = cm.overall_stat['Hamming Loss']
    cm.ZeroOneLoss = cm.overall_stat['Zero-one Loss']
    cm.NIR = cm.overall_stat['NIR']
    cm.PValue = cm.overall_stat['P-Value']
    cm.Overall_CEN = cm.overall_stat['Overall CEN']
    cm.Overall_MCEN = cm.overall_stat['Overall MCEN']
    cm.Overall_MCC = cm.overall_stat['Overall MCC']
    cm.RR = cm.overall_stat['RR']
    cm.CBA = cm.overall_stat['CBA']
    cm.AUNU = cm.overall_stat['AUNU']
    cm.AUNP = cm.overall_stat['AUNP']
    cm.RCI = cm.overall_stat['RCI']
    cm.C = cm.overall_stat['Pearson C']
    cm.SOA5 = cm.overall_stat['SOA5(Cramer)']
    cm.SOA6 = cm.overall_stat['SOA6(Matthews)']
    cm.CSI = cm.overall_stat['CSI']
    cm.ARI = cm.overall_stat['ARI']
