r语言 - 多项式回归模型，用于预测具有 500 行的变量的值

Question

大约有500个值planned在此基础上，我必须预测新值actual。

请帮我编码，在这里我展示了我正在手动做的事情：

predict(poly_reg, data.frame(planned= 48.80000,
Level2 = 48.80000^2,
Level3 = 48.80000^3))
lin_reg = lm(formula = actual ~ ., data = dataset)
summary(lin_reg)
# Fitting Polynomial Regression to the dataset
dataset$Level2 = dataset$planned^2
dataset$Level3 = dataset$planned^3
dataset$Level4 = dataset$Planned_FTM^0.25000
poly_reg = lm(formula = actual~ ., data = dataset)
# Visualising the Linear Regression results
# install.packages('ggplot2')
library(ggplot2)
ggplot() + geom_point(aes(x = dataset$planned, y = dataset$actual), colour = 'red') + geom_line(aes(x = dataset$planned, y = predict(lin_reg, newdata = dataset)), colour = 'blue') + ggtitle('Truth or Bluff (Linear Regression)') + xlab('planned') + ylab('actual')
# Predicting a new result with Linear Regression
predict(lin_reg, data.frame(planned= 48.80000))
# Predicting a new result with Polynomial Regression
predict(poly_reg, data.frame(planned= 48.80000, Level2 = 48.80000^2, Level3 = 48.80000^3)) 

Answer 1

尝试在planned上使用poly到您正在使用的任何阶多项式(我使用了 4(：

# Fitting Linear Regression to the dataset
lin_reg = lm(formula = actual ~ planned, data = dataset)
# Fitting Polynomial Regression to the dataset
poly_reg = lm(formula = actual ~ poly(planned, 4), data = dataset)
# Predicting a new result with Linear Regression
predict(lin_reg)
# Predicting a new result with Polynomial Regression
predict(poly_reg)