ts_aug_awareness: Augmentation by awareness

In tspredit: Time Series Prediction with Integrated Tuning

Augmentation by awareness

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 reinforce recent data preferably.

Usage

ts_aug_awareness(factor = 1)

Arguments

factor

increase factor for data augmentation

Value

a ts_aug_awareness object.

Examples

library(daltoolbox)
data(tsd)

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

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

tspredit documentation built on June 22, 2025, 5:07 p.m.