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 fit a generalized additive model into data:
- First, load the mgcv package, which contains the gam function:
> install.packages("mgcv")
> library(mgcv)
- Then, install the MASS package and load the Boston dataset:
> install.packages("MASS")
> library(MASS)
> attach(Boston)
> str(Boston)
- Fit the regression using gam:
> fit = gam(dis ~ s(nox))
- Get the summary information of the fitted model:
> summary(fit) Output: Family: gaussian Link function: identity Formula: dis ~ s(nox) Parametric coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.79504 0.04507 84.21 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Approximate significance of smooth ...
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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.