Datasets:
Tasks:
Time Series Forecasting
Modalities:
Text
Formats:
parquet
Size:
10K - 100K
Tags:
skycmd
License:
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End of preview. Expand in Data Studio
skycmd time series (s6-cast training)
The training series of the s6-cast forecaster: public series absent from GIFT-Eval and Chronos' zero-shot benchmark, and the state variables of the skycmd games.
Part of skycmd, tiny decision models trained from scratch in Rust that run in the
browser. Written by sky-data fetch-series and sky-train cast-synth --games at commit 84c6d854.
Licences of every set: DATA_LICENSES.md.
Each row is one series: id (<source>:<series>) and values (a list of floats, in time order).
The s6-cast trainer holds out one series in ten, by id, for validation; windows and synthetic
series (sky-train cast-synth) are drawn from these at training time.
Sources and licences
Each config is one source and keeps its source's licence (share-alike sources stay share-alike). Attribution goes to the upstream authors; the conversion is ours.
| config | upstream | licence | how it is used | rows |
|---|---|---|---|---|
games |
ours: state variables of the skycmd games (sky-train cast-synth --games) |
apache-2.0 | 60 oracle episodes per game | 1,549 |
london_smart_meters |
autogluon/chronos_datasets monash_london_smart_meters (Monash archive, Godahewa et al. 2021) |
cc-by-4.0 | first 2,000 series, last 8,192 points | 2,000 |
pedestrian_counts |
autogluon/chronos_datasets monash_pedestrian_counts (Monash archive, Godahewa et al. 2021) |
cc-by-4.0 | all series | 66 |
rideshare |
autogluon/chronos_datasets monash_rideshare (Monash archive, Godahewa et al. 2021) |
cc-by-4.0 | every numeric column of the first 200 rows | 200 |
ushcn_daily |
autogluon/chronos_datasets ushcn_daily (NOAA NCEI) |
public domain (U.S. Government work) | every numeric column of the first 1,300 rows | 1,300 |
wiki_daily |
autogluon/chronos_datasets wiki_daily_100k (Wikimedia pageviews) |
cc0-1.0 | first 5,000 series | 5,000 |
wind_farms_daily |
autogluon/chronos_datasets wind_farms_daily (Monash archive, Godahewa et al. 2021) |
cc-by-4.0 | all series, last 8,192 points | 337 |
wind_farms_hourly |
autogluon/chronos_datasets wind_farms_hourly (Monash archive, Godahewa et al. 2021) |
cc-by-4.0 | all series, last 8,192 points | 337 |
Files
| file | rows |
|---|---|
data/games.parquet |
1,549 |
data/london_smart_meters.parquet |
2,000 |
data/pedestrian_counts.parquet |
66 |
data/rideshare.parquet |
200 |
data/ushcn_daily.parquet |
1,300 |
data/wiki_daily.parquet |
5,000 |
data/wind_farms_daily.parquet |
337 |
data/wind_farms_hourly.parquet |
337 |
from datasets import load_dataset
ds = load_dataset("maxgfr/skycmd-series", "games")
skycmd wrote no row with a language model: the targets come from the upstream labels (some upstream sets carry their own teacher soft labels, see their cards), the games' oracles or our generators.
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