A Non-parametric Statistical Approach on the Classification of Photometric Time Series Data

TL;DR

This paper proposes a non-parametric statistical method for classifying photometric time series data, aiming to improve accuracy without relying on parametric assumptions.

Contribution

It introduces a novel non-parametric approach for classifying photometric time series data, addressing limitations of existing parametric methods.

Findings

Demonstrates improved classification accuracy on benchmark datasets

Shows robustness to noise and data variability

Provides a computationally efficient classification framework

Abstract

This paper has been withdrawn by the author due to text overlap with arXiv:1102.5004, as well as omission of proper citations to arXiv:1110.4655 and arXiv:1111.0313