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  1. data.test<- data.frame(
  2. "名前"=c("A","B","C","D","E"),
  3. "血液型"=c("B","A","O","AB","A"),
  4. "成績"=c(50,85,70,45,90),
  5. "体重"=c(60,80,75,40,61)
  6. )
  7. model<- lm("成績~血液型+体重",data.test)
  8. summary(model)
  9. data.test<- data.frame(
  10. "名前"=c("E","F","G"),
  11. "血液型"=c("O","A","B"),
  12. "体重"=c(60,70,50)
  13. )
  14. predict(model,newdata=data.test)
Success #stdin #stdout 0.16s 179584KB
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Standard input is empty
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Call:
lm(formula = "成績~血液型+体重", data = data.test)

Residuals:
ALL 5 residuals are 0: no residual degrees of freedom!

Coefficients:
            Estimate Std. Error t value Pr(>|t|)
(Intercept) 106.0526         NA      NA       NA
血液型AB    -50.5263         NA      NA       NA
血液型B     -40.2632         NA      NA       NA
血液型O     -16.3158         NA      NA       NA
体重         -0.2632         NA      NA       NA

Residual standard error: NaN on 0 degrees of freedom
Multiple R-squared:      1,	Adjusted R-squared:    NaN 
F-statistic:   NaN on 4 and 0 DF,  p-value: NA

       1        2        3 
73.94737 87.63158 52.63158
https://ideone.com/fcqoJ0
language:
R (R 3.5.2)
created:
7 years ago
visibility:
public

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