April 2017
Beginner to intermediate
420 pages
9h 58m
English
book
Mastering Machine Learning with R - Second Edition
by Cory Lesmeister, Doug Ortiz, Vikram Dhillon, Miroslav Kopecky
Content preview from Mastering Machine Learning with R - Second Edition
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Modeling and evaluation
As mentioned, the package that we will use is neuralnet. The function in neuralnet will call for the use of a formula as we used elsewhere, such as y~x1+x2+x3+x4, data = df. In the past, we used y~, to specify all the other variables in the data as inputs. However, neuralnet does not accommodate this at the time of writing. The way around this limitation is to use the as.formula() function. After first creating an object of the variable names, we will use this as an input in order to paste the variables properly on the right side of the equation:
> n <- names(shuttleTrain) > form <- as.formula(paste("use ~", paste(n[!n %in% "use"], collapse = " + "))) > form use ~ stability.xstab + error.MM + error.SS + error.XL ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.