Machine Learning Techniques for Circular Data: A Novel Approach for Decision Trees and Clustering

Q: How many days will it take for my paper to be published?

The review time for papers is not fixed. However, if the paper is accepted and the author completes the processing charges formalities, the paper will be published within a few working days.

Q: I would like to receive a hard copy of the journal materials. Are there any additional charges?

You can log in to the author portal and pay 500 INR to receive the hard copy materials.

Snehal Kawale

Machine Learning Techniques for Circular Data: A Novel Approach for Decision Trees and Clustering

Authors: Snehal Kawale

Unique Paper ID: 182811
Volume: 12
Issue: 2
PageNo: 3225-3227

Keywords: Circular Data Data Visualization Decision Tree for Circular Data Machine Learning for Circular Data Clustering Algorithms Rainfall Prediction.

Abstract:
Data can be broadly categorized into linear and circular types, with circular data arising when measurements are directional or angular in nature, such as wind directions or time of day. Unlike linear data, circular data exhibits a cyclical structure—values wrap around at a boundary (e.g., 0° is equivalent to 360°)—posing unique challenges for traditional statistical and machine learning methods. Circular statistics, or directional statistics, specifically address these challenges by accounting for the inherent periodicity of such data. However, existing machine learning techniques have not been adequately adapted to effectively handle circular data. This research aims to bridge this gap by developing novel algorithms and methodologies tailored for circular data analysis. By integrating machine learning with circular statistical principles, our work seeks to enhance predictive modeling and insight extraction from directional datasets, with applications spanning meteorology, biology, and beyond.

Download article

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 12
Issue: 2
PageNo: 3225-3227

Machine Learning Techniques for Circular Data: A Novel Approach for Decision Trees and Clustering

Available:https://ijirt.org/article?manuscript=182811

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now