XyGen: Synthetic data generator for feature selection[Formula presented]

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812.pdf (379.08 KB)

Date

2023-03

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Journal ISSN

Volume Title

Publisher

Elsevier B.V.

Abstract

Given the large number of feature selection algorithms, it has become imperative to have a uniform procedure for evaluating the performance of the algorithms. We propose a library of synthetic datasets designed specifically to test the effectiveness of feature selection algorithms. The datasets are inspired by applications in the field of electronics and have a range of characteristics to provide a variety of test scenarios. The software comes in the form of a Python library with standard interface for loading and generating datasets. Each dataset is implemented as a function that allows control of various parameters of the data. © 2023 The Author(s)

Description

Keywords

Data mining, Feature selection, Machine learning, Synthetic data

Citation

Kamalov, F., Elnaffar, S., Sulieman, H., & Cherukuri, A. K. (2023). XyGen: Synthetic data generator for feature selection. Software Impacts, 15, 100485. https://doi.org/10.1016/j.simpa.2023.100485

URI

https://doi.org/10.1016/j.simpa.2023.100485
 https://hdl.handle.net/20.500.12519/812

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Department of Electrical Engineering