i am using vglm for multiple logistic regression. i have 1 response variable (total 4 category) and 5 predictor. Call: vglm(formula = class ~ PC1 + PC2 + PC3 + PC4 + PC5, family = multinomial(), na.action = na.pass) Coefficients: (Intercept):1 (Intercept):2 PC1:1 PC1:2 PC2:1 -0.5480417 -1.0716498 0.5146799 0.1578941 -0.3111874 PC2:2 PC3:1 PC3:2 PC4:1 PC4:2 0.5213314 -0.9584294 -0.9889684 0.8510812 1.2110904 PC5:1 PC5:2 0.5832257 0.5126038 Degrees of Freedom: 330 Total; 318 Residual Residual Deviance: 216.9244 Log-likelihood: -108.4622 i am not understanding whether this model is good or not. what log likelihood value says ? whether it should be low or high ? because i used this model to predict the 4 category of response variable by choosing those datapoint which were used to fit the model. i get 72% of training data ( those which were used to fit model) correctly predicted. please help [[alternative HTML version deleted]]