Ionosphere
Donated on 12/31/1988
Classification of radar returns from the ionosphere
Dataset Characteristics
Multivariate
Subject Area
Physics and Chemistry
Associated Tasks
Classification
Feature Type
Integer, Real
# Instances
351
# Features
34
Dataset Information
Additional Information
This radar data was collected by a system in Goose Bay, Labrador. This system consists of a phased array of 16 high-frequency antennas with a total transmitted power on the order of 6.4 kilowatts. See the paper for more details. The targets were free electrons in the ionosphere. "Good" radar returns are those showing evidence of some type of structure in the ionosphere. "Bad" returns are those that do not; their signals pass through the ionosphere. Received signals were processed using an autocorrelation function whose arguments are the time of a pulse and the pulse number. There were 17 pulse numbers for the Goose Bay system. Instances in this databse are described by 2 attributes per pulse number, corresponding to the complex values returned by the function resulting from the complex electromagnetic signal.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| Attribute1 | Feature | Continuous | no | ||
| Attribute2 | Feature | Continuous | no | ||
| Attribute3 | Feature | Continuous | no | ||
| Attribute4 | Feature | Continuous | no | ||
| Attribute5 | Feature | Continuous | no | ||
| Attribute6 | Feature | Continuous | no | ||
| Attribute7 | Feature | Continuous | no | ||
| Attribute8 | Feature | Continuous | no | ||
| Attribute9 | Feature | Continuous | no | ||
| Attribute10 | Feature | Continuous | no |
0 to 10 of 35
Additional Variable Information
-- All 34 are continuous -- The 35th attribute is either "good" or "bad" according to the definition summarized above. This is a binary classification task.
Baseline Model Performance
Dataset Files
| File | Size |
|---|---|
| ionosphere.data | 74.7 KB |
| ionosphere.names | 3 KB |
| Index | 123 Bytes |
Papers Citing this Dataset
Sort by Year, desc
By Tomasz Maszczyk, Wlodzislaw Duch. 2019
Published in World Congress on Computational Intelligence, IEEE Press, pp. 3852-3859, 2010.
By Wenqing Su, Xiao Guo, Hai Zhang. 2019
Published in ArXiv.
By Kentaro Kanamori, Satoshi Hara, Masakazu Ishihata, Hiroki Arimura. 2019
Published in ArXiv.
By Wlodzislaw Duch, Karol Grudzi'nsk. 2018
Published in Proceedings of the International Conference on Neural Information Processing, Shanghai, 2001, Vol. I, pp. 235-240.
By Feng Li, Sibo Yang, Huanhuan Huang, Wei Wu. 2018
Published in ArXiv.
0 to 5 of 47
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset ionosphere = fetch_ucirepo(id=52) # data (as pandas dataframes) X = ionosphere.data.features y = ionosphere.data.targets # metadata print(ionosphere.metadata) # variable information print(ionosphere.variables)
Sigillito, V., Wing, S., Hutton, L., & Baker, K. (1989). Ionosphere [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5W01B.
Creators
V. Sigillito
S. Wing
L. Hutton
K. Baker
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.