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Last data update: 2014.03.03

R: Prediction method for 'hdmda' class objects.

predict.hdmda

R Documentation

Prediction method for ‘hdmda’ class objects.

Description

This function computes the class prediction of a dataset with respect to the model-based supervised classification method hdmda.

Usage

## S3 method for class 'hdmda'
predict(object, X, ...)

Arguments

`object`	An object of class ‘hdmda’.
`X`	A matrix or a data frame of observations, assuming the rows are the observations and the columns the variables. Note that NAs are not allowed.
`...`	Arguments based from or to other methods. Not currently used.

Value

`class`	vector of the predicted class.
`posterior`	The matrix of the probabilities to belong to a class for each observation and each class.

Author(s)

Laurent Berge, Charles Bouveyron and Stephane Girard

References

C. Bouveyron and C. Brunet (2014), “Model-based clustering of high-dimensional data: A review”, Computational Statistics and Data Analysis, vol. 71, pp. 52-78.

Bouveyron, C. Girard, S. and Schmid, C. (2007), “High Dimensional Discriminant Analysis”, Communications in Statistics: Theory and Methods, vol. 36 (14), pp. 2607-2623.

Bouveyron, C. Celeux, G. and Girard, S. (2011), “Intrinsic dimension estimation by maximum likelihood in probabilistic PCA”, Pattern Recognition Letters, vol. 32 (14), pp. 1706-1713.

Berge, L. Bouveyron, C. and Girard, S. (2012), “HDclassif: An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data”, Journal of Statistical Software, 46(6), pp. 1-29, url: http://www.jstatsoft.org/v46/i06/.

Hastie, T., & Tibshirani, R. (1996), “Discriminant analysis by Gaussian mixtures”, Journal of the Royal Statistical Society, Series B (Methodological), pp. 155-176.

Examples

# Load the Wine data set
data(wine)
cls = wine[,1]; X = scale(wine[,-1])

# A simple use...
out = hdmda(X[1:100,],cls[1:100])
res = predict(out,X[101:nrow(X),])

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(HDclassif)
Loading required package: MASS
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/HDclassif/predict.hdmda.Rd_%03d_medium.png", width=480, height=480)
> ### Name: predict.hdmda
> ### Title: Prediction method for 'hdmda' class objects.
> ### Aliases: predict.hdmda
> ### Keywords: ~kwd1 ~kwd2
> 
> ### ** Examples
> 
> # Load the Wine data set
> data(wine)
> cls = wine[,1]; X = scale(wine[,-1])
> 
> # A simple use...
> out = hdmda(X[1:100,],cls[1:100])
> res = predict(out,X[101:nrow(X),])
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>