ts_aug_awaresmooth {tspredit}

Augmentation by awareness smooth

Description

Time series data augmentation is a technique used to increase the size and diversity of a time series dataset by creating new instances of the original data through transformations or modifications. The goal is to improve the performance of machine learning models trained on time series data by reducing overfitting and improving generalization. Awareness Smooth reinforce recent data preferably. It also smooths noise data.

Usage

ts_aug_awaresmooth(factor = 1)

Arguments

factor

increase factor for data augmentation

Value

a ts_aug_awaresmooth object.

Examples

library(daltoolbox)
data(sin_data)

#convert to sliding windows
xw <- ts_data(sin_data$y, 10)

#data augmentation using awareness
augment <- ts_aug_awaresmooth()
augment <- fit(augment, xw)
xa <- transform(augment, xw)
ts_head(xa)