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tips_labelled <- tips %>% set_variable_labels( day = "Day of the week", time = "Lunch or Dinner", total_bill = "Bill's total" )#给变量添加标签 mod_labelled <- lm(tip ~ day + time + total_bill, data = tips_labelled) ggcoef_model(mod_labelled) 还可以通过将命名向量传递给varia...
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ggbivariate(tips, outcome = "smoker", explanatory = c("day","time","sex","tip")) ggbivariate(tips, outcome = "total_bill", explanatory = c("day", "time", "sex", "tip")) ggbivariate(tips, "smoker") 自定义颜色 终于可以直接和ggplot2对接了! library(ggplot2) ggbivariate(tips, out...
ggbivariate(tips, outcome ="smoker", explanatory = c("day","time","sex","tip")) + scale_fill_brewer(type ="qual") 这个函数当然也可以直接用ggplot2的语法修改主题,就不在赘述了。 ggnostic() 这个函数可以直接可视化回归模型。 使用之前医学统计学系列中例15-1的数据: ...
GGML tips & tricks If your issue is with model generation quality, then please at least scan the following links and papers to understand the limitations of LLaMA models. This is especially important when choosing an appropriate model size and appreciating both the significant and subtle differences...
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