Title: Analysis of high dimensional data using feature selection models

Authors: Shubham Mahajan; Amit Kant Pandit

Addresses: School of Electronics & Communication, Shri Mata Vaishno Devi University, Katra – 182320, India ' School of Electronics & Communication, Shri Mata Vaishno Devi University, Katra – 182320, India

Abstract: The determination of features assumes a significant part in enhancing the output of AI models, limiting the computational time taken to make a learning model and improving the exactness of the learning cycle. Hence, analysts give more consideration to the determination of features to expand the exhibition of AI calculations. The choice of the proper technique for the determination of features is significant for a specific AI task through high-dimensional information. It is subsequently important to complete an examination on various strategies for character determination for the exploration network, specifically to improve effective techniques for choice. Method for choosing features to improve the effectiveness of AI undertakings for high-dimensional information. This paper gives the whole writing survey of the different techniques for choosing features for high-dimensional information to accomplish this target.

Keywords: feature selection; signal processing; artificial intelligence; high dimensional data; classification; signal processing; learning models; classifiers.

DOI: 10.1504/IJNT.2023.131106

International Journal of Nanotechnology, 2023 Vol.20 No.1/2/3/4, pp.116 - 128

Received: 09 Feb 2021
Accepted: 07 Jun 2021
Published online: 31 May 2023 *