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rknn (version 1.0)

internal functions: Random KNN Internal Functions

Description

Some internal and under-development functions

Usage

factorial.bigz(n)
    chooses.bigz(n, m)
    choose.bigz(n, m)
    set.return.seed(Random.seed=NULL, seed=NULL)
    
    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)    rknn.FNN(data, y, k=5, r=500, mtry=trunc(sqrt(ncol(data))))
    rknn.dist(data, r=500, k=1, mtry=trunc(sqrt(ncol(data))), y=NULL)
    pressresid(obj)

Arguments

n
Number of elements in a set chosen from.
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.
data
A data matrix.
y
A vector of responses.
k
Number of nearest neighbors.
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.
Random.seed
A seed in the .Random.seed format.
seed
An integer seed.
criterion
either uses mean_accuracy or mean_support for best.
obj
A linear model.