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Using machine learning in R

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  • 346 3
    Using machine learning in R while generating formula ~. ,data,

    what does . indicate

    for example

    fit <- svm(factor(outcome)~., data= train, probability= T)
pre <- predict(fit, test, decision.value= T, probability= T)​
      August 30, 2021 1:11 PM IST
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  • 461
    Simply put, machine learning allows the user to feed a computer algorithm an immense amount of data and have the computer analyze and make data-driven recommendations and decisions based on only the input data.

    Machine learning is made up of three parts:

    • The computational algorithm at the core of making determinations.
    • Variables and features that make up the decision.
    • Base knowledge for which the answer is known that enables (trains) the system to learn.
      September 17, 2021 1:10 PM IST
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  • 131 2
    The help page (?formula) can shed some light regarding . interpretation :

    There are two special interpretations of . in a formula. The usual one is in the context of a data argument of model fitting functions and means ‘all columns not otherwise in the formula’: see terms.formula. In the context of update.formula, only, it means ‘what was previously in this part of the formula’.

    However, note that . is used differently by reshape and reshape2 packages:
    ?cast
    There are a couple of special variables: "..." represents all other variables not used in the formula and "." represents no variable
      August 31, 2021 3:43 PM IST
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  • 259
    The dot means "everything else". I.e. say you're dataset has the variables x , y and z then y~. would get translated to y ~ x + z
      September 1, 2021 1:49 PM IST
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