提供给离散比例ggplot2的连续值答案

【问题标题】：Continuous value supplied to discrete scale ggplot2提供给离散比例ggplot2的连续值
【发布时间】：2023-03-06 22:01:01
【问题描述】：

当我尝试在 R 中绘制决策边界图时，遇到了一些问题，它返回了错误“提供给离散尺度的连续值”。我认为问题发生在 scale_colur_manual 中，但我不知道如何解决。下面附上代码。

library(caTools)
set.seed(123)
split = sample.split(df$Purchased,SplitRatio = 0.75)
training_set = subset(df,split==TRUE)
test_set = subset(df,split==FALSE)

# Feature Scaling
training_set[,1:2] = scale(training_set[,1:2])
test_set[,1:2] = scale(test_set[,1:2])

# Fitting logistic regression to the training set
lr = glm(formula = Purchased ~ .,
         family = binomial,
         data = training_set)

 #Predicting the test set results
 prob_pred = predict(lr,type = 'response',newdata = test_set[-3])
 y_pred = ifelse(prob_pred > 0.5, 1, 0)

 #Making the Confusion Matrix
 cm = table(test_set[,3],y_pred)
 cm

 #Visualizing the training set results
 library(ggplot2)

 set = training_set

 X1 = seq(min(set[, 1]) - 1, max(set[, 1]) + 1, by = 0.01)

 X2 = seq(min(set[, 2]) - 1, max(set[, 2]) + 1, by = 0.01)

 grid_set = expand.grid(X1, X2)

 colnames(grid_set) = c('Age', 'EstimatedSalary')

 prob_set = predict(lr, type = 'response', newdata = grid_set)

 y_grid = ifelse(prob_set > 0.5, 1,0)


 ggplot(grid_set) +

       geom_tile(aes(x = Age, y = EstimatedSalary, fill = factor(y_grid)),

       show.legend = F) +

 geom_point(data = set, aes(x = Age, y = EstimatedSalary, color = Purchased),

         show.legend = F) +

 scale_fill_manual(values = c("orange", "springgreen3")) +

 scale_colour_manual(values = c("red3", "green4")) +

 scale_x_continuous(breaks = seq(floor(min(X1)), ceiling(max(X2)), by = 1)) +

 labs(title = "Logistic Regression (Training set)",

      ylab = "Estimated Salary", xlab = "Age")

【问题讨论】：

如果您包含一个简单的reproducible example 以及可用于测试和验证可能的解决方案的示例输入，则更容易为您提供帮助。删除重现问题所不需要的任何代码。
您的错误不是来自scale_color_manual，而是来自scale_x_continuous。如果我不得不猜测，我会说您的变量“Age”不是数字格式，或者您的 X1 和 X2 也不是数字格式（但我猜测第一个选项）。正如 MrFlick 所要求的，您应该提供一个可重现的数据集示例。

标签： r ggplot2

【解决方案1】：

您的Purchased 变量是一个因素吗？如果不是，它必须是。试试这个：

grid_set %>%
   mutate(Purchased=factor(Purchased)) %>%
   ggplot() + 
   geom_tile(aes(x = Age, y = EstimatedSalary, fill = factor(y_grid)),
       show.legend = F) + ... # add the rest of your commands.

【讨论】：