DSRegressor_SlidingWindow {stream} | R Documentation |
DSRegressor_SlidingWindow – Data Stream Regressor Using a Sliding Window
Description
The Regressor keeps a sliding window for the stream and rebuilds a regression model at regular
intervals. By default is builds a decision tree using lm()
.
Usage
DSRegressor_SlidingWindow(formula, model = stats::lm, window, rebuild, ...)
Arguments
formula |
a formula for the classification problem. |
model |
regression model (that has a formula interface). |
window |
size of the sliding window. |
rebuild |
interval (number of points) for rebuilding the regression. Set rebuild to
|
... |
additional parameters are passed on to the regressor (default is |
Details
This constructor creates a regressor based on DST_SlidingWindow
. The regressor has
a update()
and predict()
method.
Value
An object of class DST_SlidingWindow
.
Author(s)
Michael Hahsler
See Also
Other DSRegressor:
DSRegressor()
Examples
library(stream)
# create a data stream for the iris dataset
data <- iris[sample(nrow(iris)), ]
stream <- DSD_Memory(data)
# define the stream Regressor.
cl <- DSRegressor_SlidingWindow(
Sepal.Length ~ Petal.Length + Petal.Length,
window = 50,
rebuild = 10
)
cl
# update the regressor with 100 points from the stream
update(cl, stream, 100)
# predict the class for the next 50 points
newdata <- get_points(stream, n = 50)
pr <- predict(cl, newdata)
pr
plot(pr, newdata$Sepal.Length)
abline(0, 1, col = "red")
# get the tree model
get_model(cl)
[Package stream version 2.0-2 Index]