Statlog (Shuttle)
The shuttle dataset contains 9 attributes all of which are numerical. Approximately 80% of the data belongs to class 1
Dataset Characteristics
Multivariate
Subject Area
Physics and Chemistry
Associated Tasks
Classification
Feature Type
Integer
# Instances
58000
# Features
7
Dataset Information
Additional Information
Approximately 80% of the data belongs to class 1. Therefore the default accuracy is about 80%. The aim here is to obtain an accuracy of 99 - 99.9%. The examples in the original dataset were in time order, and this time order could presumably be relevant in classification. However, this was not deemed relevant for StatLog purposes, so the order of the examples in the original dataset was randomised, and a portion of the original dataset removed for validation purposes.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| Rad Flow | Feature | Integer | no | ||
| Fpv Close | Feature | Integer | no | ||
| Fpv Open | Feature | Integer | no | ||
| High | Feature | Integer | no | ||
| Bypass | Feature | Integer | no | ||
| Bpv Close | Feature | Integer | no | ||
| Bpv Open | Feature | Integer | no | ||
| class | Target | Integer | no |
0 to 8 of 8
Additional Variable Information
The shuttle dataset contains 9 attributes all of which are numerical. The first one being time. The last column is the class which has been coded as follows : 1 Rad Flow 2 Fpv Close 3 Fpv Open 4 High 5 Bypass 6 Bpv Close 7 Bpv Open
Baseline Model Performance
Dataset Files
| File | Size |
|---|---|
| shuttle.tst | 375.3 KB |
| shuttle.trn.Z | 312.4 KB |
| shuttle.doc | 1.2 KB |
| Index | 146 Bytes |
Reviews
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset statlog_shuttle = fetch_ucirepo(id=148) # data (as pandas dataframes) X = statlog_shuttle.data.features y = statlog_shuttle.data.targets # metadata print(statlog_shuttle.metadata) # variable information print(statlog_shuttle.variables)
Statlog (Shuttle) [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5WS31.
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.