SUSY
Donated on 2/11/2014
This is a classification problem to distinguish between a signal process which produces supersymmetric particles and a background process which does not.
Dataset Characteristics
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Subject Area
Physics and Chemistry
Associated Tasks
Classification
Feature Type
Real
# Instances
5000000
# Features
-
Dataset Information
Additional Information
Provide all relevant informatioThe data has been produced using Monte Carlo simulations. The first 8 features are kinematic properties measured by the particle detectors in the accelerator. The last ten features are functions of the first 8 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest in using deep learning methods to obviate the need for physicists to manually develop such features. Benchmark results using Bayesian Decision Trees from a standard physics package and 5-layer neural networks and the dropout algorithm are presented in the original paper. The last 500,000 examples are used as a test set.n about your data set.
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 18
Additional Variable Information
The first column is the class label (1 for signal, 0 for background), followed by the 18 features (8 low-level features then 10 high-level features):: lepton 1 pT, lepton 1 eta, lepton 1 phi, lepton 2 pT, lepton 2 eta, lepton 2 phi, missing energy magnitude, missing energy phi, MET_rel, axial MET, M_R, M_TR_2, R, MT2, S_R, M_Delta_R, dPhi_r_b, cos(theta_r1). For detailed information about each feature see the original paper.
Dataset Files
| File | Size |
|---|---|
| SUSY.csv.gz | 879.6 MB |
Reviews
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset susy = fetch_ucirepo(id=279) # data (as pandas dataframes) X = susy.data.features y = susy.data.targets # metadata print(susy.metadata) # variable information print(susy.variables)
Whiteson, D. (2014). SUSY [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C54606.
Creators
Daniel Whiteson
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.