Data files you will find here https://github.com/hse-aml/hadron-collider-machine-learning/releases/tag/Week_3

training.csv - all features

check_agreement.csv - all features besides mass for agreement check

check_correlation.csv - all features for correlation check

test.csv - all features besides mass

the goal is to design prediction model that will give best score (ROC AUC) and will meet the constraints of

• similar performance on simulated and real data (agreement check)
• decorrelation with the mass (correlation check)

the predictions over test.csv (i.e. submission file) should be sent to coursera for evaluation.

training.csv

This is a labelled dataset (the label ‘signal’ being ‘1’ for signal events, ‘0’ for background events) to train the classifier. Signal events have been simulated, while background events are real data.

This real data is collected by the LHCb detectors observing collisions of accelerated particles with a specific mass range in which τ → 3μ can’t happen. We call these events “background” and label them 0.

FlightDistance - Distance between τ and PV (primary vertex, the original protons collision point).

FlightDistanceError - Error on FlightDistance.

mass - reconstructed τ candidate invariant mass, which is absent in the test samples.

LifeTime - Life time of tau candidate.

IP - Impact Parameter of tau candidate.

IPSig - Significance of Impact Parameter.

VertexChi2 - χ2 of τ vertex.

dira - Cosine of the angle between the τ momentum and line between PV and tau vertex.

pt - transverse momentum of τ.

DOCAone - Distance of Closest Approach between p0 and p1.

DOCAtwo - Distance of Closest Approach between p1 and p2.

DOCAthree - Distance of Closest Approach between p0 and p2.

IP_p0p2 - Impact parameter of the p0 and p2 pair.

IP_p1p2 - Impact parameter of the p1 and p2 pair.

isolationa - Track isolation variable.

isolationb - Track isolation variable.

isolationc - Track isolation variable.

isolationd - Track isolation variable.

isolatione - Track isolation variable.

isolationf - Track isolation variable.

iso - Track isolation variable.

CDF1 - Cone isolation variable.

CDF2 - Cone isolation variable.

CDF3 - Cone isolation variable.

production - source of τ. This variable is absent in the test samples.

ISO_SumBDT - Track isolation variable.

p0_IsoBDT - Track isolation variable.

p1_IsoBDT - Track isolation variable.

p2_IsoBDT - Track isolation variable.

p0_track_Chi2Dof - Quality of p0 muon track.

p1_track_Chi2Dof - Quality of p1 muon track.

p2_track_Chi2Dof - Quality of p2 muon track.

p0_pt - Transverse momentum of p0 muon.

p0_p - Momentum of p0 muon.

p0_eta - Pseudorapidity of p0 muon.

p0_IP - Impact parameter of p0 muon.

p0_IPSig - Impact Parameter Significance of p0 muon.

p1_pt - Transverse momentum of p1 muon.

p1_p - Momentum of p1 muon.

p1_eta - Pseudorapidity of p1 muon.

p1_IP - Impact parameter of p1 muon.

p1_IPSig - Impact Parameter Significance of p1 muon.

p2_pt - Transverse momentum of p2 muon.

p2_p - Momentum of p2 muon.

p2_eta - Pseudorapidity of p2 muon.

p2_IP - Impact parameter of p2 muon.

p2_IPSig - Impact Parameter Significance of p2 muon.

SPDhits - Number of hits in the SPD detector.

min_ANNmuon - Muon identification. LHCb collaboration trains Artificial Neural Networks (ANN) from informations from RICH, ECAL, HCAL, Muon system to distinguish muons from other particles. This variables denotes the minimum of the three muons ANN. min ANNmuon should not be used for training. This variable is absent in the test samples.

signal - This is the target variable for you to predict in the test samples.