Plotting classification prediction (K-nearest neighbor)-CodePudding

Im trying to plot my predictions using the k-nearest neighbor method but am unable to do do, I get an error message as seen below. Im sure it's something to do with how ive set up my plot but unsure as to how i need to change it. Dataset is here;

CodePudding user response：

To get a plot similar to the one in the question, you can create a grid of prediction points to produce the background classification map, then plot the test data on top using ggplot.

# Create prediction data frame for test data
preds <- data.frame(X1 = xTest[,1], X2 = xTest[,2], Group = yTestPred)

# Create classification grid
gr <- expand.grid(X1 = seq(min(classification[,1]), max(classification[,1]),
                       length.out = 100),
                  X2 = seq(min(classification[,2]), max(classification[,2]),
                       length.out = 100))
gr$Group <- predict(kmeans_mod, newdata = gr)

# Plot the result
library(ggplot2)

ggplot(gr, aes(X1, X2, col = Group))  
  geom_point(size = 0.6)  
  geom_point(data = preds, shape = 21, aes(fill = Group), 
             col = "black", size = 3)  
  theme_minimal(base_size = 16)

Though you may prefer a raster:

library(ggplot2)

ggplot(gr, aes(X1, X2, fill = Group))  
  geom_raster(alpha = 0.3)  
  geom_point(data = preds, shape = 21, col = "black", size = 3)  
  theme_minimal(base_size = 16)

And you may wish to color the test data points with their actual level rather than their predicted level to get a visual impression of the model accuracy:

library(ggplot2)

ggplot(gr, aes(X1, X2, fill = Group))  
  geom_raster(alpha = 0.3)  
  geom_point(data = within(preds, Group <- factor(yTest)),
             col = "black", size = 3, shape = 21)  
  theme_minimal(base_size = 16)