machine learning - Code for analyzing thresholds in R model output -

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i have textual classification problem consists of 2 categories- 0 one. until tried solving creating document term matrix, , run through svm (using rtexttools package). here's code snippet: (in r)

models <- train_models(container, algorithms=c("svm")) results <- classify_models(container, models) analytics <- create_analytics(container, results) view(summary(analytics))  >>algorithm performance  >>svm_precision    svm_recall    svm_fscore  >>         0.64          0.63          0.63

my questions follows:

1.why predicted values in result matrix between 0.5-1? isn't supposed 0-1?

2.supposed have theta threshold separate scores above of class 1, , rest 0. how can analyze (in r) under theta these precision , recall values being calculated? how can change threshold different values?

3.how can create in r 2 different thresholds values each class (with what's left in between labeled "unidentified")?


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