File size: 1,754 Bytes
0a665df | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | # Dataset information: the entry point for dataset configuration, including file locations for each modality.
dataset_id: LeageST
dataset_name: LargeST
domain: traffic_management
sample_defination:
sample_type: traffic flow monitoring sensor
sample_id_graph: ID2 # Corresponding column name in the data; use None if the index is used directly.
sample_id_time_series: ID # Corresponding column name in the data; use None if the index is used directly.
description: each sample corresponds to a traffic flow monitoring sensor
modalities:
# Available feature modalities.
meta_features: # Static metadata, analogous to tabular data; read ca_meta.csv from the main directory.
required: true # meta_features is required.
file_name: ca_meta.csv # All provided files should be directly readable by pandas as a pd.DataFrame.
node_level_task_graphs:
available: true # Whether a graph for node-level tasks is available; if so, load its data from the corresponding directory.
graph_ids:
- road_distance_graph # Graph name, for example road_distance_graph (shortest driving distance graph).
time_series:
available: true # Whether time series data is available; if so, load it from the corresponding directory.
time_series_ids:
- traffic_flow # Time series name, for example traffic_flow (traffic volume).
tasks: # Task construction.
# Supported task types, for example meta_feature prediction, time series forecasting, and ranking.
- lane_count_regression # Lane count regression.
- traffic_flow_forecasting # Traffic flow forecasting.
# Data source information.
license:
data_license: source-dependent
redistribution_allowed: true
source:
name: Citi Bike Trip History
url: source url or citation |