參考文章：https://www.r-bloggers

> CarData = read.table('car.data',sep=',',col.names=c('buying','maintenance','doors','persons','lug_boot','safety','rating')) > summary(CarData)buying ? ?maintenance ? doors ? ? persons ? ? lug_boot ? ?safety ? ? ?rating ? ?high :432 ? high :432 ? 2 ? ?:432 ? 2 ? :576 ? big ?:576 ? high:576 ? acc ?: 384 ?low ?:432 ? low ?:432 ? 3 ? ?:432 ? 4 ? :576 ? med ?:576 ? low :576 ? good : ?69 ?med ?:432 ? med ?:432 ? 4 ? ?:432 ? more:576 ? small:576 ? med :576 ? unacc:1210 ?vhigh:432 ? vhigh:432 ? 5more:432 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? vgood: ?65 ? > logisticModel <- glm(rating!='unacc' ~ buying + maintenance + doors + persons + lug_boot +safety, + ? ? ? ? ? ? ? ? ? ? ?family=binomial(link = "logit"),data=CarData) ? ? ? ? ? ? ??> summary(logisticModel)Call: glm(formula = rating != "unacc" ~ buying + maintenance + doors +?persons + lug_boot + safety, family = binomial(link = "logit"),?data = CarData)Deviance Residuals:?Min ? ? ? 1Q ? Median ? ? ? 3Q ? ? ?Max ? -3.2160 ? 0.0000 ? 0.0000 ? 0.0257 ? 2.4336 ?Coefficients:Estimate Std. Error z value Pr(>|z|) ? ? (Intercept) ? ? ? -28.4255 ?1257.5255 ?-0.023 ? ?0.982 ? ? buyinglow ? ? ? ? ? 5.0481 ? ? 0.5670 ? 8.904 ?< 2e-16 *** buyingmed ? ? ? ? ? 3.9218 ? ? 0.4842 ? 8.100 5.49e-16 *** buyingvhigh ? ? ? ?-2.0662 ? ? 0.3747 ?-5.515 3.49e-08 *** maintenancelow ? ? ?3.4064 ? ? 0.4692 ? 7.261 3.86e-13 *** maintenancemed ? ? ?3.4064 ? ? 0.4692 ? 7.261 3.86e-13 *** maintenancevhigh ? -2.8254 ? ? 0.4145 ?-6.816 9.36e-12 *** doors3 ? ? ? ? ? ? ?1.8556 ? ? 0.4042 ? 4.591 4.41e-06 *** doors4 ? ? ? ? ? ? ?2.4816 ? ? 0.4278 ? 5.800 6.62e-09 *** doors5more ? ? ? ? ?2.4816 ? ? 0.4278 ? 5.800 6.62e-09 *** persons4 ? ? ? ? ? 29.9652 ?1257.5256 ? 0.024 ? ?0.981 ? ? personsmore ? ? ? ?29.5843 ?1257.5255 ? 0.024 ? ?0.981 ? ? lug_bootmed ? ? ? ?-1.5172 ? ? 0.3758 ?-4.037 5.40e-05 *** lug_bootsmall ? ? ?-4.4476 ? ? 0.4750 ?-9.363 ?< 2e-16 *** safetylow ? ? ? ? -30.5045 ?1300.3428 ?-0.023 ? ?0.981 ? ? safetymed ? ? ? ? ?-3.0044 ? ? 0.3577 ?-8.400 ?< 2e-16 *** --- Signif. codes: ?0 ��***�� 0.001 ��**�� 0.01 ��*�� 0.05 ��.�� 0.1 �� �� 1(Dispersion parameter for binomial family taken to be 1)Null deviance: 2110.47 ?on 1727 ?degrees of freedom Residual deviance: ?339.36 ?on 1712 ?degrees of freedom AIC: 371.36Number of Fisher Scoring iterations: 21

.com/learn-logistic-regression-and-beyond/

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