Classify by Mixture Discriminant Analysis
Classify observations in conjunction with mda.
## S3 method for class 'mda' predict(object, newdata, type, prior, dimension, g, ...)
object |
a fitted mda object. |
newdata |
new data at which to make predictions. If missing, the training data is used. |
type |
kind of predictions: |
prior |
the prior probability vector for each class; the default is the training sample proportions. |
dimension |
the dimension of the space to be used, no larger
than the dimension component of |
g |
??? |
... |
further arguments to be passed to or from methods. |
An appropriate object depending on type. object has a
component fit which is regression fit produced by the
method argument to mda. There should be a
predict method for this object which is invoked. This method
should itself take as input object and optionally newdata.
data(glass) samp <- sample(1:nrow(glass), 100) glass.train <- glass[samp,] glass.test <- glass[-samp,] glass.mda <- mda(Type ~ ., data = glass.train) predict(glass.mda, glass.test, type = "post") # abbreviations are allowed confusion(glass.mda, glass.test)
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