HLCM {FRESA.CAD}

Latent class based modeling of binary outcomes

Description

Modeling a binary outcome via the the discovery of latent clusters. Each discovered latent cluster is modeled by the user provided fit function. Discovered clusters will be modeled by KNN or SVM.

Usage

	HLCM(formula = formula, 
	                data=NULL,
	                method=BSWiMS.model,
	                hysteresis = 0.1,
					classMethod=KNN_method,
					classModel.Control=NULL,
					minsize=10,
	                ...
					)

Arguments

formula

the base formula to extract the outcome

data

the data to be used for training the method

method

the binary classification function

hysteresis

the hysteresis shift for detecting wrongly classified subjects

classMethod

the function name for modeling the discovered latent clusters

classModel.Control

the parameters to be passed to the latent-class fitting function

minsize

the minimum size of the discovered clusters

...

parameters for the classification function

Value

original

The original model trained with all the dataset

alternativeModel

The model used to classify the wrongly classified samples

classModel

The method that models the latent class

accuracy

The original accuracy

selectedfeatures

The character vector of selected features

hysteresis

The used hysteresis

classSet

The discovered class label of each sample

Author(s)

Jose G. Tamez-Pena

See Also

class::knn