A forecaster for sales data
Project description
forecast_ensemble
forecast_ensemble combines multiple models into a single forecast and returns a combined package of models, their evaluated results including a composite score
Usage
The forecast is run using main.py
with the following options
Request Requirements
The required input format is a JSON with the following fields:
Required:
data_filepath
: filepath of the time series data to run the ensemble ontarget_column
: name of the input columnaggregate_operation
: string operation to apply to target_column to create the time seriesoutput_directory
: directory to return the result JSON to
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for amendment_forecast-0.1.22.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | b9be8cdda3abf2d680f7d0e324014ce8a4d40eee28445bf455eb2ab9be20bf66 |
|
MD5 | 6be3acc1e6c3e7aa9cbadc7a035d34e3 |
|
BLAKE2b-256 | a98a567974ec8307021bc76abe928708a0aad4402db868b1f8cf6c6e6bc156cf |
Close
Hashes for amendment_forecast-0.1.22-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 51e33877e8ae2efd3f55410985754c45289afd17fabf554f0377170ced8f5739 |
|
MD5 | 2ba86c1e879b6b1279301d0d5e8b9241 |
|
BLAKE2b-256 | ce15cdf4f0fc63f7d1b730a22fde12f1d946707c47031da830755261018b268d |