Question

我使用MLR包的plotLearnerPrediction函数生成了一些不错的图。我能够对返回的ggplot进行一些调整（参见下面的代码）。但我不知道如何进行最后一次调整。也就是说，我想根据标签（示例图中的组）更改数据点的颜色。

Another produced plot (overlapping data points)

这是我的代码的最后一个版本（通常是for循环的一部分）：

plot <- plotLearnerPrediction(learner = learner_name, task = tasks[[i]], cv = 0,
                              pointsize = 1.5, gridsize = 500) + 
  ggtitle(trimws(sprintf("Predictions %s %s", meta$name[i], meta$nr[i])), 
          subtitle = sprintf("DR = %s, ML = %s, CV =  LOO, ACC = %.2f", meta$type[i], 
                             toupper(strsplit(learner_name, "classif.")[[1]][2]), acc[[i]])) + 
  xlab(sprintf("%s 1", lab)) + 
  ylab(sprintf("%s 2", lab)) + 
  scale_fill_manual(values = colors) +
  theme(plot.title = element_text(size = 18, face = "bold"),
        plot.subtitle = element_text(size = 12, face = "bold", colour = "grey40"),
        axis.text.x = element_text(vjust = 0.5, hjust = 1),
        axis.text = element_text(size = 14, face = "bold"),
        axis.title.x = element_text(vjust = 0.5),
        axis.title = element_text(size = 16, face = "bold"),
        #panel.grid.minor = element_line(colour = "grey80"),
        axis.line.x = element_line(color = "black", size = 1),
        axis.line.y = element_line(color = "black", size = 1),
        panel.grid.major = element_line(colour = "grey80"),
        panel.background = element_rect(fill = "white"),
        legend.justification = "top",
        legend.margin = margin(l = 0),
        legend.title = element_blank(),
        legend.text = element_text(size = 14))

以下是plotLearnerPrediction函数源代码的一部分。我想要否决geom_point（color =＆＃34; black＆＃34;）。在我的代码中添加简单的geom_point（color =＆＃34; pink＆＃34;）不会为数据点着色，而是整个绘图。是否有解决方案用颜色向量否决该代码？可能还需要更改aes（）以根据组更改颜色。

        else if (taskdim == 2L) {
        p = ggplot(mapping = aes_string(x = x1n, y = x2n))
        p = p + geom_tile(data = grid, mapping = aes_string(fill = target))
        p = p + scale_fill_gradient2(low = bg.cols[1L], mid = bg.cols[2L], 
            high = bg.cols[3L], space = "Lab")
        p = p + geom_point(data = data, mapping = aes_string(x = x1n, 
            y = x2n, colour = target), size = pointsize)
        p = p + geom_point(data = data, mapping = aes_string(x = x1n, 
            y = x2n), size = pointsize, colour = "black", 
            shape = 1)
        p = p + scale_colour_gradient2(low = bg.cols[1L], 
            mid = bg.cols[2L], high = bg.cols[3L], space = "Lab")
        p = p + guides(colour = FALSE)
    }

Answer 1

plotLearnerPrediction()函数返回ggplot绘图对象，允许进行某种程度的自定义，而无需修改源代码。在您的特定情况下，您可以使用scale_fill_manual()设置自定义填充颜色：

library(mlr)
g = plotLearnerPrediction(makeLearner("classif.randomForest"), iris.task)
g + scale_fill_manual(values = c("yellow", "orange", "red"))

Answer 2

你总是可以攻击gg对象。以下适用于ggplot2 2.2.1，并为所有geom_point图层添加手动alpha值。

library(mlr)
library(ggplot2)
g = plotLearnerPrediction(makeLearner("classif.qda"), iris.task)
ids.geom.point = which(sapply(g$layers, function(z) class(z$geom)[[1]]) == "GeomPoint")
for(i in ids.geom.point) {
  g$layers[[i]]$aes_params$alpha = 0.1
}
g

更改颜色数据点plotLearnerPrediction（MLR包）

2 个答案: