View source: R/DSRegressor_SlidingWindow.R
DSRegressor_SlidingWindow | R Documentation |
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()
.
DSRegressor_SlidingWindow(formula, model = stats::lm, window, rebuild, ...)
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 |
This constructor creates a regressor based on DST_SlidingWindow
. The regressor has
a update()
and predict()
method.
An object of class DST_SlidingWindow
.
Michael Hahsler
Other DSRegressor:
DSRegressor()
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)
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