I'm using the support vector machine from the e1071 package to classify my data and want to visualize how the machine actually does the classification. However, when using the plot.svm function, I get an error that I can't resolve.
Script:
library("e1071")
data <-read.table("2010223_11042_complete")
names(data) <- c("Class","V1", "V2")
model <- svm(Class~.,data, type = "C-classification", kernel = "linear")
plot(model,data,fill=TRUE, grid=200, svSymbol=4, dataSymbol=1, color.palette=terrain.colors)
Output:
plot(model,data,fill=TRUE, grid=200, svSymbol=4, dataSymbol=1, color.palette=terrain.colors)
Error in rect(0, levels[-length(levels)], 1, levels[-1L], col = col) :
cannot mix zero-length and non-zero-length coordinates
Traceback:
traceback()
4: rect(0, levels[-length(levels)], 1, levels[-1L], col = col)
3: filled.contour(xr, yr, matrix(as.numeric(preds), nr = length(xr),
byrow = TRUE), plot.axes = {
axis(1)
axis(2)
colind <- as.numeric(model.response(model.frame(x, data)))
dat1 <- data[-x$index, ]
dat2 <- data[x$index, ]
coltmp1 <- symbolPalette[colind[-x$index]]
coltmp2 <- symbolPalette[colind[x$index]]
points(formula, data = dat1, pch = dataSymbol, col = coltmp1)
points(formula, data = dat2, pch = svSymbol, col = coltmp2)
}, levels = 1:(length(levels(preds)) + 1), key.axes = axis(4,
1:(length(levels(preds))) + 0.5, labels = levels(preds),
las = 3), plot.title = title(main = "SVM classification plot",
xlab = names(lis)[2], ylab = names(lis)[1]), ...)
2: plot.svm(model, data, fill = TRUE, grid = 200, svSymbol = 4,
dataSymbol = 1, color.palette = terrain.colors)
1: plot(model, data, fill = TRUE, grid = 200, svSymbol = 4,
dataSymbol = 1, color.palette = terrain.colors)
Part of my (4488 lines long) data file:
-1 0 23.532
+1 1 61.1157
+1 1 61.1157
+1 1 61.1157
-1 1 179.03
-1 0 17.0865
-1 0 27.6201
-1 0 17.0865
-1 0 27.6201
-1 1 89.6398
-1 0 42.7418
-1 1 89.6398
Since I`m just starting with R, I have no idea what this means and how I should deal with it, nor did I find anything useful in other places.