Generating Three-class Data with 50 Predictors

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Description

Randomly generate data for a three-class model.

Usage

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ex1data(n.data, p=50)

Arguments

n.data

number of data samples.

p

number of predictors.

Details

The data is generated based on Example 1 described in Wang (2012).

Value

A list with n.data by p predictor matrix x, three-class response y and conditional probabilities.

Author(s)

Zhu Wang

References

Zhu Wang (2012), Multi-class HingeBoost: Method and Application to the Classification of Cancer Types Using Gene Expression Data. Methods of Information in Medicine, 51(2), 162–7.

Examples

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## Not run: 
dat <- ex1data(100, p=5)
mhingebst(x=dat$x, y=dat$y)

## End(Not run)