| Name : R-OSTSC
| |
| Version : 0.0.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.1.13
| Date : 2024-06-14 11:42:06
|
| Group : Development/Libraries/Other
| Source RPM : R-OSTSC-0.0.1-lp153.1.13.src.rpm
|
| Size : 1.08 MB
| |
| Packager : (none)
| |
| Summary : Over Sampling for Time Series Classification
|
Description :
Oversampling of imbalanced univariate time series classification data
using integrated ESPO and ADASYN methods. Enhanced Structure Preserving Oversampling
(ESPO) is used to generate a large percentage of the synthetic minority samples
from univariate labeled time series under the modeling assumption that the predictors
are Gaussian. ESPO estimates the covariance structure of the minority-class samples
and applies a spectral filer to reduce noise. Adaptive Synthetic (ADASYN) sampling
approach is a nearest neighbor interpolation approach which is subsequently applied
to the ESPO samples. This code is ported from a \'MATLAB\' implementation by Cao et al.
< doi:10.1109/TKDE.2013.37> and adapted for use with Recurrent Neural Networks
implemented in \'TensorFlow\'.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
