Description Usage Arguments Value Author(s) References See Also Examples
For msc.kd
and msc.svm
ompute probabilities for
each crystal in the Morse-Smale complex for each point in X based on a
kernel density estimat or and one-against all svm
. For
msc.lm
,msc.slm
and msc.slm.elnet
the prediction based on the fitted regression models.
1 2 3 4 5 6 7 8 9 10 | ## S3 method for class 'msc.kd'
predict(object, newdata, addExtrema=TRUE, ...)
## S3 method for class 'msc.svm'
predict(object, newdata, ...)
## S3 method for class 'msc.lm'
predict(object, newdata, ...)
## S3 method for class 'msc.slm'
predict(object, newdata, ...)
## S3 method for class 'msc.slm.elnet'
predict(object, newdata, ...)
|
object |
Morse-Smale complex object. |
newdata |
Observations to predict, if missing the sample form the Morse-Smale complex are used. |
addExtrema |
Add the extrema indices of this partion (default TRUE) |
... |
Further arguments are ignored in these functions |
For Morse-Smale complex objects a (number of points) x (number of partitions) matrix with probabilities $p(C_i|x)$ of belonging to each crystal. For regression model objects the predicted function values.
Samuel Gerber
[1] Samuel Gerber and Kristin Potter The Morse-Smale Complex for Data Analysis, Journal of Statistical Software, 2012, vol. 50, no. 2, pp 1-22
[2] Samuel Gerber, Oliver Ruebel Peer-Timo Bremer, Valerio Pascucci, Ross Whitaker, Morse-Smale Regression, Journal of Computational and Graphical Statistics, 2012
[3] Samuel Gerber, Peer-Timo Bremer, Valerio Pascucci, Ross Whitaker, Visual Exploration of High Dimensional Scalar Functions, IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp 1271-1280, Nov.-Dec. 2010.
David M. Mount and Sunil Arya ANN library http://www.cs.umd.edu/~mount/ANN/
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