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https://github.com/soheshdoshi/forcastmodel
This Model is Base On Halt & Winter Algorithm.This Model is Forecast About Seasonal Data.
https://github.com/soheshdoshi/forcastmodel
forcasting machine-learning numpy python
Last synced: about 2 months ago
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This Model is Base On Halt & Winter Algorithm.This Model is Forecast About Seasonal Data.
- Host: GitHub
- URL: https://github.com/soheshdoshi/forcastmodel
- Owner: soheshdoshi
- Created: 2018-03-17T16:39:46.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-04-15T08:42:23.000Z (over 6 years ago)
- Last Synced: 2023-12-11T08:12:28.301Z (about 1 year ago)
- Topics: forcasting, machine-learning, numpy, python
- Language: Python
- Homepage:
- Size: 10.7 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# ForecastModel in Python
This Model is Base On Halt & Winter Algorithm.This Model is Forecast For Seasonal Data.
## What's included?
* mean Function
* average Funcation
* moving_average Funcation
* weighted_average Funcation
* exponential_smoothing Funcation
* double_exponential_smoothing Funcation
* triple_exponential_smoothing Funcation
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system
### Prerequisites
What things you need to install the software and how to install them
```
Python 3.x
matplotlib 2.2.2
numpy 1.14.2
```
### Installing
([Windows Machine](https://www.youtube.com/watch?v=yrRmLOcB9fg)
([Linux Machine](http://docs.python-guide.org/en/latest/starting/install3/linux/))
([Mac Machine](http://programwithus.com/learn-to-code/install-python3-mac/))
## How to Run
```
python first_script.py
```
## Contributing
If you want to implement, please follow the following steps:
1. First, comment on the issue for that function you want to implement.
2. On Github, fork the repository (see [this article](https://help.github.com/articles/fork-a-repo/)).
3. Clone the repository to your local machine (see [this article](https://help.github.com/articles/cloning-a-repository/)).
4. Create a new branch with `git checkout -b [function-name]`.
5. Commit you work (using `git add [file]` and `git commit`).
6. Push your commit to your repository on Github (using `git push`).
7. Submit a pull request on the repository, requesting that your code be merged into the repository (see [this article](https://help.github.com/articles/creating-a-pull-request/)).
8. Wait for your pull request to be merged into master.
Thank you for any contributions!
## Authors
**Sohesh Doshi**