我正在进行逻辑回归，我注意到向量中的每个唯一字符串都接收到自己的参数。 R是否根据向量内每个唯一值的集合优化结果变量的预测？
library(stats)
df = as.data.frame( matrix(c("a","a","b","c","c","b","a","a","b","b","c",1,0,0,0,1,0,1,1,0,1,0,1,0,100,10,8,3,5,6,13,10,4,"SF","CHI","NY","NY","SF","SF","CHI","CHI","SF","CHI","NY"), ncol = 4))
colnames(df) = c("letter","number1","number2","city")
df$letter = as.factor(df$letter)
df$city = as.factor(df$city)
df$number1 = as.numeric(df$number1)
df$number2 = as.numeric(df$number2)
glm(number1 ~ .,data=df)
#Call: glm(formula = number1 ~ ., data = df)
#Coefficients:
# (Intercept) letterb letterc number2 cityNY citySF
#1.57191 -0.25227 -0.01424 0.04593 -0.69269 -0.20634
#Degrees of Freedom: 10 Total (i.e. Null); 5 Residual
#Null Deviance: 2.727
#Residual Deviance: 1.35 AIC: 22.14
以上示例中的Logit处理城市如何？