Dear List,
I'm quite new to R and want to do logistic regression with a 200K
feature data set (around 150 training examples).
I'm aware that I should use Naive Bayes but I have a more general
question about the capability of R handling very high dimensional data.
Please consider the following R code where "mygenestrain.tab" is a 150
by 200000 matrix:
traindata <- read.table('mygenestrain.tab');
mylogit <- glm(V1 ~ ., data = traindata, family = "binomial");
When executing this code I get the following error:
Error in terms.formula(formula, data = data) :
allocMatrix: too many elements specified
Calls: glm ... model.frame -> model.frame.default -> terms -> terms.formula
Execution halted
Is this because R can't handle 200K features or am I doing something
completely wrong here?
Thanks a lot for your help!
best Regards,
Romeo
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