icr.formula
From caret v4.48
by Max Kuhn
Independent Component Regression
Fit a linear regression model using independent components
- Keywords
- multivariate
Usage
## S3 method for class 'formula':
icr(formula, data, weights, ..., subset, na.action, contrasts = NULL)
## S3 method for class 'default':
icr(x, y, ...)## S3 method for class 'icr':
predict(object, newdata, ...)
Arguments
- formula
- A formula of the form
class ~ x1 + x2 + ...
- data
- Data frame from which variables specified in
formula
are preferentially to be taken. - weights
- (case) weights for each example -- if missing defaults to 1.
- subset
- An index vector specifying the cases to be used in the training sample. (NOTE: If given, this argument must be named.)
- na.action
- A function to specify the action to be taken if
NA
s are found. The default action is for the procedure to fail. An alternative is na.omit, which leads to rejection of cases with missing values on any required variable. (NOTE: If given, this - contrasts
- a list of contrasts to be used for some or all of the factors appearing as variables in the model formula.
- ...
- arguments passed to
fastICA
- x
- matrix or data frame of
x
values for examples. - y
- matrix or data frame of target values for examples.
- object
- an object of class
icr
as returned byicr
. - newdata
- matrix or data frame of test examples.
Details
This produces a model analogous to Principal Components Regression (PCR) but uses Independent Component Analysis (ICA) to produce the scores. The user must specify a value of n.comp
to pass to fastICA
.
The function preProcess
to produce the ICA scores for the original data and for newdata
.
Value
- For
icr
, a list with elements model the results of lm
after the ICA transformationica pre-processing information n.comp number of ICA components names column names of the original data
See Also
Examples
data(BloodBrain)
icrFit <- icr(bbbDescr, logBBB, n.comp = 5)
icrFit
predict(icrFit, bbbDescr[1:5,])
Community examples
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