higgs_25: 200 Simulated particles to emulate Higgs boson discovery

In andeek/forestr: Random forests with a user created splitting criterion

Description

A dataset containing simulated data produced using Monte Carlo to resemble properties measured by particle detectors in an accelerator to detect the Higgs Boson particle. This dataset created by sampling observations to ensure the percentage of unbalancedness is 25

Usage

data(higgs_25)

Format

A data frame with 200 rows and 29 variables:

class

presence of Higgs boson particle, 1 for signal, 0 for background

lepton_pT

low-

lepton_eta

low-level feature

lepton_phi

low-level feature

missing_energy_magnitude

low-level feature

missing_energy_phi

low-level feature

jet_1_pt

low-level feature

jet_1_eta

low-level feature

jet_1_phi

low-level feature

jet_1_b_tag

low-level feature

jet_2_pt

low-level feature

jet_2_eta

low-level feature

jet_2_phi

low-level feature

jet_2_b_tag

low-level feature

jet_3_pt

low-level feature

jet_3_eta

low-level feature

jet_3_phi

low-level feature

jet_3_b_tag

low-level feature

jet_4_pt

low-level feature

jet_4_eta

low-level feature

jet_4_phi

low-level feature

jet_4_b_tag

low-level feature

m_jj

high-level feature

m_jjj

high-level feature

m_lv

high-level feature

m_jlv

high-level feature

m_bb

high-level feature

m_wbb

high-level feature

m_wwbb

high-level feature

Source

https://archive.ics.uci.edu/ml/datasets/HIGGS

andeek/forestr documentation built on May 12, 2019, 2:40 a.m.