R: Random KNN Internal Functions

internal functions {rknn} | R Documentation

## Random KNN Internal Functions

### Description

Some internal and under-development functions

### Usage

        rbyb(p, m, eta)
        rbyp(p, m, eta)
        rbyv(p, m, nu)
        rbyz(p, m)
        rbyz.sim(p, m, nsim=1000)
        rbyz.geo(p, m=floor(sqrt(p)), rmax=p)
        rbylambda(p, m, lambda=1)
        knn(train, test, cl, k=1)
        knn.cv (train, cl, k=1)
        knn.reg(train, test = NULL, y, k = 3)
        pressresid(obj)

### Arguments

`m` | Number of elements in a subset to be drawn.
`p` | Total number of available features.
`mtry` | Number of features to be drawn for each KNN.
`eta` | Coverage Probability.
`nu` | mean mutiplicity of a feature
`rmax` | number of series terms for independent geometric approximation
`nsim` | number of simulations for geometric simulation.
`lambda` | mean number of silient features.
`samples` | A vector of indice for a set of observations.
`cl` | A factor for classification labels.
`train` | A data matrix.
`test` | A data matrix.
`y` | A vector of responses.
`k` | Number of nearest neighbors.
`cl` | A vector of class labels.
`K` | Number of folds for cross-validation.
`pk` | A real number between 0 and to indicate the proportion of the feature set to be kept in each step.
`r` | Number of KNN to be generated.
`seed` | An integer seed.
`criterion` | either uses mean_accuracy or mean_support for best.
`obj` | A linear model.

### Author(s)

Shengqiao Li<lishengqiao@yahoo.com>

[Package rknn version 1.2-1 Index]