Depending on the classifier a list including (the ni and est are common for all classifiers):
shapeA matrix with the shape parameters.
scaleA matrix with the scale parameters.
expmuA matrix with the mean parameters.
sigmaA matrix with the (MLE, hence biased) variance parameters.
locationA matrix with the location parameters (medians).
scaleA matrix with the scale parameters.
meanA matrix with the scale parameters.
varA matrix with the variance parameters.
aA matrix with the "alpha" parameters.
bA matrix with the "beta" parameters.
niThe sample size of each group in the dataset.
estThe estimated group of the xnew observations. It returns a numerical value back regardless of the target
variable being numerical as well or factor. Hence, it is suggested that you do \"as.numeric(ina)\" in order to
see what is the predicted class of the new data.