ESPOBar: Generate samples by ESPO algorithm.
In lweicdsor/OSTSC: Over Sampling for Time Series Classification
Description
Usage
Arguments
Value
Description
Generate samples by ESPO algorithm.
Usage
1
ESPOBar(me, v, dMod, p, n, r, m, numToGen)
Arguments
me
Mean vector of positive class
v
Eigen axes matrix (Each axis is a column vector)
dMod
Modified Eigen Spectrum Value
p
The minority class samples
n
The majority class samples
r
scalar specifies which level (towards the boundary) we shall push the synthetic data,
with the default value = 1
m
Scalar specifies the reliable portion of the eigen spectrum
numToGen
The number of samples to be generated
Value
sampleESPO
lweicdsor/OSTSC documentation built on May 8, 2019, 1:13 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value
Description
Generate samples by ESPO algorithm.
Usage
1 | ESPOBar(me, v, dMod, p, n, r, m, numToGen)
|
Arguments
me |
Mean vector of positive class |
v |
Eigen axes matrix (Each axis is a column vector) |
dMod |
Modified Eigen Spectrum Value |
p |
The minority class samples |
n |
The majority class samples |
r |
scalar specifies which level (towards the boundary) we shall push the synthetic data, with the default value = 1 |
m |
Scalar specifies the reliable portion of the eigen spectrum |
numToGen |
The number of samples to be generated |
Value
sampleESPO
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.