Hi everyone, I'm new to using R and I have an assignment in which I'm supposed to use SVM modeling for the classification of credit approval. I am using ksvm from the package kernlab per my professor's request. This is the dataset that I am using UCI Machine Learning Repository.
This is what I have so far:
`data$V16 <- as.factor(data$V16)
model <- ksvm(as.matrix(data[,1:15]), data[,16], type="C-svc",
kernel="vanilladot", C=100, scaled=TRUE)`
My professor said not to worry about splitting the data into train and test sets because we are not there yet. I keep getting the error: Error in if (any(co)) { : missing value where TRUE/FALSE needed . I've been looking for ways to fix it but all I can find is to change the class attribute to a factor which I have but it still throws the error anyway. I also checked if there were any null values in the dataset by using sum(is.na(data) to see if that was the issue but it returned 0.
Yes of course here are the first 10 rows:
V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16
1 b 30.83 0.000 u g w v 1.250 t t 1 f g 00202 0 +
2 a 58.67 4.460 u g q h 3.040 t t 6 f g 00043 560 +
3 a 24.50 0.500 u g q h 1.500 t f 0 f g 00280 824 +
4 b 27.83 1.540 u g w v 3.750 t t 5 t g 00100 3 +
5 b 20.17 5.625 u g w v 1.710 t f 0 f s 00120 0 +
6 b 32.08 4.000 u g m v 2.500 t f 0 t g 00360 0 +
7 b 33.17 1.040 u g r h 6.500 t f 0 t g 00164 31285 +
8 a 22.92 11.585 u g cc v 0.040 t f 0 f g 00080 1349 +
9 b 54.42 0.500 y p k h 3.960 t f 0 f g 00180 314 +
10 b 42.50 4.915 y p w v 3.165 t f 0 t g 00052 1442 +
I also tried to convert the data type according to the .names file from the website where I downloaded the data, but even after converting the data types it still gave me the same error.
