问题描述
是否有一种压缩" lm类的对象的方法，以便可以将其保存到磁盘中，并稍后加载以供predict.lm使用?
Is there a way to 'compress' an object of class lm, so that I can save it to the disk and load it up later for use with predict.lm?
我有一个lm对象，保存后最终达到142mb，而且我很难相信预报.lm需要所有原始观测值/拟合值/残差等来进行线性预测.我可以删除信息以使保存的模型更小吗?
I have an lm object that ends up being ~142mb upon saving, and I have a hard time believing that predict.lm needs all of the original observations / fitted values / residuals etc. to make a linear prediction. Can I remove information so that the saved model is smaller?
我尝试将某些变量(fitted.values，residuals等)设置为NA，但这似乎对保存的文件大小没有影响.
I have tried setting some of the variables (fitted.values, residuals, etc.) to NA, but it seems to have no effect on the saved file size.
推荐答案
您可以使用biglm拟合模型，biglm模型对象小于lm模型对象.您可以使用predict.biglm创建一个函数，该函数可以将newdata设计矩阵传递至该函数，该函数将返回预测值.
You can use biglm to fit your models, a biglm model object is smaller than a lm model object. You can use predict.biglm create a function that you can pass the newdata design matrix to, which returns the predicted values.
另一种选择是使用saveRDS保存文件，这些文件看起来比较小，因为它们作为单个对象的开销较小，而不是像save那样可以保存多个对象.
Another option is to use saveRDS to save the files, which appear to be slightly smaller, as they have less overhead, being a single object, not like save which can save multiple objects.
library(biglm)
m <- lm(log(Volume)~log(Girth)+log(Height), trees)
mm <- lm(log(Volume)~log(Girth)+log(Height), trees, model = FALSE, x =FALSE, y = FALSE)
bm <- biglm(log(Volume)~log(Girth)+log(Height), trees)
pred <- predict(bm, make.function = TRUE)
save(m, file = 'm.rdata')
save(mm, file = 'mm.rdata')
save(bm, file = 'bm.rdata')
save(pred, file = 'pred.rdata')
saveRDS(m, file = 'm.rds')
saveRDS(mm, file = 'mm.rds')
saveRDS(bm, file = 'bm.rds')
saveRDS(pred, file = 'pred.rds')
file.info(paste(rep(c('m','mm','bm','pred'),each=2) ,c('.rdata','.rds'),sep=''))
# size isdir mode mtime ctime atime exe
# m.rdata 2806 FALSE 666 2013-03-07 11:29:30 2013-03-07 11:24:23 2013-03-07 11:29:30 no
# m.rds 2798 FALSE 666 2013-03-07 11:29:30 2013-03-07 11:29:30 2013-03-07 11:29:30 no
# mm.rdata 2113 FALSE 666 2013-03-07 11:29:30 2013-03-07 11:24:28 2013-03-07 11:29:30 no
# mm.rds 2102 FALSE 666 2013-03-07 11:29:30 2013-03-07 11:29:30 2013-03-07 11:29:30 no
# bm.rdata 592 FALSE 666 2013-03-07 11:29:30 2013-03-07 11:24:34 2013-03-07 11:29:30 no
# bm.rds 583 FALSE 666 2013-03-07 11:29:30 2013-03-07 11:29:30 2013-03-07 11:29:30 no
# pred.rdata 1007 FALSE 666 2013-03-07 11:29:30 2013-03-07 11:24:40 2013-03-07 11:29:30 no
# pred.rds 995 FALSE 666 2013-03-07 11:29:30 2013-03-07 11:27:30 2013-03-07 11:29:30 no
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