MiniBooNE particle identification
Donated on 12/12/2010
This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background).
Dataset Characteristics
Multivariate
Subject Area
Physics and Chemistry
Associated Tasks
Classification
Feature Type
Real
# Instances
130065
# Features
-
Dataset Information
Additional Information
The submitted file is set up as follows. In the first line is the the number of signal events followed by the number of background events. The signal events come first, followed by the background events. Each line, after the first line has the 50 particle ID variables for one event.
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Description | Units | Missing Values |
|---|---|---|---|---|---|
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no | |||||
| no |
0 to 10 of 50
Additional Variable Information
50 particle ID variables (real) for each event.
Dataset Files
| File | Size |
|---|---|
| MiniBooNE_PID.txt | 87 MB |
Reviews
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset miniboone_particle_identification = fetch_ucirepo(id=199) # data (as pandas dataframes) X = miniboone_particle_identification.data.features y = miniboone_particle_identification.data.targets # metadata print(miniboone_particle_identification.metadata) # variable information print(miniboone_particle_identification.variables)
Roe, B. (2005). MiniBooNE particle identification [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5QC87.
Creators
Byron Roe
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.