October 2017
Beginner to intermediate
572 pages
26h 1m
English
book
Machine Learning with R Cookbook - Second Edition
by AshishSingh Bhatia, Yu-Wei, Chiu (David Chiu)
Content preview from Machine Learning with R Cookbook - Second Edition
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How to do it...
Perform the following steps to predict values with linear regression:
- Fit a linear model with the x and y1 variables:
> lmfit = lm(y1~x, Quartet)
- Assign values to be predicted into newdata:
> newdata = data.frame(x = c(3,6,15))
- Compute the prediction result using the confidence interval with level set as 0.95:
> predict(lmfit, newdata, interval="confidence", level=0.95) Output: fit lwr upr 1 4.500364 2.691375 6.309352 2 6.000636 4.838027 7.163245 3 10.501455 8.692466 12.310443
- Compute the prediction result using this prediction interval:
> predict(lmfit, newdata, interval="predict") Output: fit lwr upr 1 4.500364 1.169022 7.831705 2 6.000636 2.971271 9.030002 3 10.501455 7.170113 13.832796
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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.