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-0.1.12.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 999e5a28b43051deb56a4d1696205dd07afb7d04682618abb09fda2ad11ac012 |
|
MD5 | be2622627630166281d3c7ca1aeaadf5 |
|
BLAKE2b-256 | 2cfd931b2934714ac7634575d363f36c32ab6200f692250ee92546de97290374 |
Close
Hashes for amendment_forecast-0.1.12-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 46c41453a72ebf7b098a6b833efde621b8b8ae61d2f8f69f422ea6b222397532 |
|
MD5 | 8e4d34bc71fe048cd18249f8fa7b0539 |
|
BLAKE2b-256 | 8cc9cfc8679c6d8f2601580e24030ee1f0c0c6de127ddecb266f830e2763b06c |