predict

predict,VSLCMresults-method

instance of <code><a href="/link/?package=VarSelLCM&version=2.1.3.1" vslcmresults'="" data-mini-rdoc="VarSelLCM::"></a>'>VSLCMresults</code>.

object

data.frame of the observations to classify.

newdata

the type of prediction: probability of classification (probability) or the partition (partition)

type

This function gives the probabilities of classification for new observations by using the mixture model fit with the function <code><a rd-options="" href="/link/VarSelCluster?package=VarSelLCM&version=2.1.3.1" data-mini-rdoc="VarSelLCM::VarSelCluster">VarSelCluster</a></code>.

Full model selection (detection of the relevant features and estimation of the number of clusters) for model-based clustering (see reference here <doi:10.1007/s11222-016-9670-1>). Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing values can occur and do not necessitate any pre-processing. Shiny application permits an easy interpretation of the results.

Mohammed Sedki

VarSelLCM

Variable Selection for Model-Based Clustering of Mixed-Type Data
Set with Missing Values

predict function

instance of <code><a href='<a href='VSLCMresults'></a>'>VSLCMresults</a></code>.

This function gives the probabilities of classification for new observations by using the mixture model fit with the function <code><a rd-options='' href='VarSelCluster'>VarSelCluster</a></code>.

predict: Prediction of the cluster memberships

Description

Usage

Arguments

Value