On Oct 27, 2009, at 6:02 AM, Grzes wrote:
Hi everybody!
I want to find a closer neighbourins observation. This is my code:
##########################
library(klaR)
library(ipred)
library(mlbench)
data(PimaIndiansDiabetes2)
dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)]
dane[,2]=log(dane[,2])
dane[,1:2]=scale(dane[,1:2])
zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F)
klasyfikatorKNN=ipredknn(diabetes~glucose
+insulin,data=dane,subset=zbior.uczacy,k=3)
oceny=predict(klasyfikatorKNN,dane[-zbior.uczacy,],"class")
#data frames with my result from klasyfikatorKNN
df=data.frame(glucose=c(klasyfikatorKNN$learn$X[,
1]),insulin=klasyfikatorKNN$learn$X[,2],diabetes=c(klasyfikatorKNN
$learn$y))
#And picture
drawparti(as.factor(df$diabetes), df$glucose, df$insulin, method =
"sknn",
prec = 100, xlab = NULL, ylab = NULL)
I get an error: Error: could not find function "drawparti"
##########################
My question is: How or where may I find correct or wrong values
which were
drawn (found,classification) in this picture?
No picture resulted.
It means I'm looking for x, y
values.
Not sure exactly what you are asking. Does this modification to df and
fairly obvious the cross table help?
> df=data.frame(glucose=c(klasyfikatorKNN$learn$X[,
1]),insulin=klasyfikatorKNN$learn$X[,2],pred.diabetes=klasyfikatorKNN
$learn$y, trueDiab=dane[,3])
Warning message:
In data.frame(glucose = c(klasyfikatorKNN$learn$X[, 1]), insulin =
klasyfikatorKNN$learn$X[, :
row names were found from a short variable and have been discarded
> with( df, table(pred.diabetes, trueDiab))
trueDiab
pred.diabetes neg pos
neg 174 86
pos 88 44
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______________________________________________
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