predict.enpls.en: Make Predictions from a Fitted Ensemble Partial Least Squares...

In wind22zhu/enpls1.2: Ensemble Partial Least Squares Regression

Description

This function make predictions on new data by fitted enpls.en object.

Usage

## S3 method for class 'enpls.en'
predict(object, newx, ...)

Arguments

object	An object of class enpls.en.
newx	new data to predict with
...	Other parameters to be passed on to predict.

Details

This function make predictions on new data by fitted enpls.en object.

Value

A numeric vector containing the predicted values.

Author(s)

Min-feng Zhu <[e-mail]>, Nan Xiao <[e-mail]>

References

Dongsheng Cao, Yizeng Liang, Qingsong Xu, Yifeng Yun, and Hongdong Li. "Toward better QSAR/QSPR modeling: simultaneous outlier detection and variable selection using distribution of model features." Journal of computer-aided molecular design 25, no. 1 (2011): 67–80.

See Also

See enpls.en for performing ensemble PLS regression.

Examples

data(alkanes)
x = alkanes$x
y = alkanes$y

set.seed(42)
enpls.fit = enpls.en(x, y, MCtimes = 10)
y.pred = predict(enpls.fit, newx = x)$ypred
plot(y, y.pred, xlim = range(y), ylim = range(y))
abline(a = 0L, b = 1L)

wind22zhu/enpls1.2 documentation built on May 4, 2019, 6:31 a.m.