I am working on a text classification problem with the text2vec package and caret. I am using text2vec to build a document-term matrix before building different models with caret. The goal is to identify string similarity between two strings, using labeled training data.
However, when training a linear SVM model, I get a number of warning messages, excerpt below:
Warning messages: 1: In svm.default(x = as.matrix(x), y = y, kernel = "linear", ... :
Variable(s) ‘influenza’ and ‘perindoprilindapamide’ and ‘bisoprololhct.1’ and ‘creon.1’ and ‘kreon.1’ and ‘paratramadol.1’ constant. Cannot scale data.
Can you please help me to understand these warnings and how to address Cannot scale data?
An excerpt of the original Training Data:
ID MAKTX_Keyword PH_Level_04_Keyword Result
266325638 AMLODIPINE AMLODIPINE 0
724712821 IRBESARTANHCTZ IRBESARTANHCTZ 0
567428641 RABEPRAZOLE RABEPRAZOLE 0
137472217 MIRTAZAPINE MIRTAZAPINE 0
175827784 FONDAPARINUX ARIXTRA 1
456372747 VANCOMYCIN VANCOMYCIN 0
653832438 BRUFEN IBUPROFEN 1
917575539 POTASSIUM POTASSIUM 0
222949123 DIOSMINHESPERIDIN DIOSMINHESPERIDIN 0
892725684 IBUPROFEN IBUPROFEN 0
Code to build SVM Model:
control <- trainControl(method="repeatedcv", number=10, repeats=3, savePredictions=TRUE, classProbs=TRUE)
Train_PRDHA_String.df$Result <- ifelse(Train_PRDHA_String.df$Result == 1, "X", "Y")
(warn=1)
(warnings=2)
t1 = Sys.time()
svm_Linear <- train(x = as.matrix(dtm_train), y = as.factor(Train_PRDHA_String.df$Result),
method = "svmLinear2",
trControl=control,
tuneLength = 5,
metric ="Accuracy")
print(difftime(Sys.time(), t1, units = 'sec'))
It means, when these variables are resampled, they only have one unique value. You can use preProc = "zv" to get rid of the warning.