ESPO

Eigen axes matrix (Each axis is a column vector)

dMod

A scalar ratio specifies which level (towards the boundary) we shall push the synthetic data, 
with the default value 1

Scalar specifies the reliable portion of the eigen spectrum

The number of samples to be generated

numToGen

Generate samples by ESPO algorithm.

internal

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'.

ESPO: Generate samples by ESPO algorithm.

Description

Usage

Arguments

Value