/EAIWS23

Emergent Algorithmic Intelligence Winter School 2023

Primary LanguageJupyter Notebook

EAIWS23

Emergent Algorithmic Intelligence Winter School 2023

Predictive Challenge

The data can be downloaded here:

Submission

The pickle file data/prediction_example.pkl contains an example of a valid submission. Please provide your submission by mail in the same format. A single column with the same MultiIndex as the example file. The column name does not matter.

Variables

Variable Description Available Measurements
date Date of the measurement (hourly levels) YYYY-MM-DD HH:MM:SS
state The state where the measurement was taken string
city The city where the measurement was taken string
PM2.5_target Target variable (One hour ahead PM2.5) ug/m3
PM2.5 Particulate matter 2.5 ug/m3
CO Carbon monoxide mg/m3
CO2 Carbon dioxide mg/m3
NO Nitric oxide ug/m3
NO2 Nitrogen dioxide ug/m3
NOx Nitrogen oxides ppb
NH3 Ammonia ug/m3
SO2 Sulfur dioxide ug/m3
Temp Temperature °C
AT Air temperature °C
BP Barometric pressure mmHg
Benzene Concentration of Benzene in the air ug/m3
CH4 Methane ug/m3
Eth-Benzene Concentration of Ethylbenzene in the air ug/m3
HCHO Formaldehyde ug/m3
Hg Mercury ug/m3
MH Mixing height m
MP-Xylene Concentration of Meta-Para-Xylene in the air ug/m3
NMHC Non-methane hydrocarbons ug/m3
O Xylene Concentration of Ortho-Xylene in the air ug/m3
Ozone Ozone concentration ug/m3
Power Power consumption W
RF Rainfall mm
RH Relative humidity %
SPM Suspended particulate matter ug/m3
SR Solar radiation W/m2
THC Total hydrocarbons ug/m3
Toluene Concentration of Toluene in the air ug/m3
VWS Vertical Wind speed m/s
WD Wind direction degree
WS Wind speed m/s
Xylene Concentration of Xylene in the air ug/m3

The goal is to predict PM2.5_target, the one-hour ahead PM2.5 concentration, on the test set.

This data is a modification of publicly available data. Please do not use the original data set for your solution.