Data
ATLAS-Higgs-Boson-Machine-Learning-Challenge-2014

ATLAS-Higgs-Boson-Machine-Learning-Challenge-2014

active ARFF Public Domain (CC0) Visibility: public Uploaded 04-06-2023 by Matthias Feurer
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
This is the datasets from the Kaggle Higgs Boson Machine Learning Challenge 2014. The data was downloaded from the [CERN website](http://opendata.cern.ch/record/328), which also hosts the documentation of the data. Further information about the challenge can be found on [Kaggle](https://www.kaggle.com/competitions/higgs-boson/), [the challenge website](https://higgsml.ijclab.in2p3.fr), and the [PMLR competition proceedings](http://proceedings.mlr.press/v42/). Note: This version encodes -999 as NaN.

31 features

Label (target)nominal2 unique values
0 missing
EventId (row identifier)numeric818238 unique values
0 missing
DER_mass_MMCnumeric177621 unique values
124602 missing
DER_mass_transverse_met_lepnumeric131888 unique values
0 missing
DER_mass_visnumeric154516 unique values
0 missing
DER_pt_hnumeric190925 unique values
0 missing
DER_deltaeta_jet_jetnumeric7664 unique values
580253 missing
DER_mass_jet_jetnumeric197974 unique values
580253 missing
DER_prodeta_jet_jetnumeric21893 unique values
580253 missing
DER_deltar_tau_lepnumeric5018 unique values
0 missing
DER_pt_totnumeric84683 unique values
0 missing
DER_sum_ptnumeric285774 unique values
0 missing
DER_pt_ratio_lep_taunumeric7464 unique values
0 missing
DER_met_phi_centralitynumeric2830 unique values
0 missing
DER_lep_eta_centralitynumeric1001 unique values
580253 missing
PRI_tau_ptnumeric86459 unique values
0 missing
PRI_tau_etanumeric4979 unique values
0 missing
PRI_tau_phinumeric6286 unique values
0 missing
PRI_lep_ptnumeric88725 unique values
0 missing
PRI_lep_etanumeric5003 unique values
0 missing
PRI_lep_phinumeric6286 unique values
0 missing
PRI_metnumeric126055 unique values
0 missing
PRI_met_phinumeric6286 unique values
0 missing
PRI_met_sumetnumeric348080 unique values
0 missing
PRI_jet_numnumeric4 unique values
0 missing
PRI_jet_leading_ptnumeric152061 unique values
327371 missing
PRI_jet_leading_etanumeric8902 unique values
327371 missing
PRI_jet_leading_phinumeric6286 unique values
327371 missing
PRI_jet_subleading_ptnumeric75078 unique values
580253 missing
PRI_jet_subleading_etanumeric8932 unique values
580253 missing
PRI_jet_subleading_phinumeric6286 unique values
580253 missing
PRI_jet_all_ptnumeric207428 unique values
0 missing
Weight (ignore)numeric339549 unique values
0 missing
KaggleSet (ignore)nominal4 unique values
0 missing
KaggleWeight (ignore)numeric340497 unique values
0 missing

19 properties

818238
Number of instances (rows) of the dataset.
31
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
5168486
Number of missing values in the dataset.
594664
Number of instances with at least one value missing.
30
Number of numeric attributes.
1
Number of nominal attributes.
3.23
Percentage of binary attributes.
72.68
Percentage of instances having missing values.
20.38
Percentage of missing values.
0.55
Average class difference between consecutive instances.
96.77
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
3.23
Percentage of nominal attributes.
65.83
Percentage of instances belonging to the most frequent class.
538678
Number of instances belonging to the most frequent class.
34.17
Percentage of instances belonging to the least frequent class.
279560
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Label
Define a new task