ADASYN: Generate samples by ADASYN approach.
In OSTSC: Over Sampling for Time Series Classification
Description
Usage
Arguments
Value
Description
Generate samples by ADASYN approach.
Usage
1
ADASYN(p, n, nTarget, k, m)
Arguments
p
minority class samples
n
majority class samples
nTarget
the targeted number of samples to achieve
k
is the number of nearest neighbours in the ADASYN algorithm, with the default value of 5
m
seeds from the positive class in k-NN of the ADASYN algorithm, with the default value of 15
Value
sampleADA
OSTSC documentation built on May 2, 2019, 5:16 a.m.
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Description Usage Arguments Value
Description
Generate samples by ADASYN approach.
Usage
1 | ADASYN(p, n, nTarget, k, m)
|
Arguments
p |
minority class samples |
n |
majority class samples |
nTarget |
the targeted number of samples to achieve |
k |
is the number of nearest neighbours in the ADASYN algorithm, with the default value of 5 |
m |
seeds from the positive class in k-NN of the ADASYN algorithm, with the default value of 15 |
Value
sampleADA
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.
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