guess: Guess
In chasset/grnn: General regression neural network
Description
Usage
Arguments
See Also
Examples
Description
Infers the value of a new observation.
Usage
1
guess(nn, X)
Arguments
nn
A trained and smoothed General regression
neural network.
X
A vector describing a new observation.
See Also
Examples
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n <- 100
set.seed(1)
x <- runif(n, -2, 2)
y0 <- x^3
epsilon <- rnorm(n, 0, .1)
y <- y0 + epsilon
grnn <- learn(data.frame(y,x))
grnn <- smooth(grnn, sigma=0.1)
guess(grnn, -2)
guess(grnn, -1)
guess(grnn, -0.2)
guess(grnn, -0.1)
guess(grnn, 0)
guess(grnn, 0.1)
guess(grnn, 0.2)
guess(grnn, 1)
guess(grnn, 2)
chasset/grnn documentation built on April 1, 2020, 9:27 p.m.
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Description Usage Arguments See Also Examples
Description
Infers the value of a new observation.
Usage
1 | guess(nn, X)
|
Arguments
nn |
A trained and smoothed General regression neural network. |
X |
A vector describing a new observation. |
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | n <- 100
set.seed(1)
x <- runif(n, -2, 2)
y0 <- x^3
epsilon <- rnorm(n, 0, .1)
y <- y0 + epsilon
grnn <- learn(data.frame(y,x))
grnn <- smooth(grnn, sigma=0.1)
guess(grnn, -2)
guess(grnn, -1)
guess(grnn, -0.2)
guess(grnn, -0.1)
guess(grnn, 0)
guess(grnn, 0.1)
guess(grnn, 0.2)
guess(grnn, 1)
guess(grnn, 2)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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