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Hyperparameter tuning

This library works best with hyperparameter tuning. Slightly different parameters can give significantly different results.

Installation

This library is available on git. It can be installed with

Introduction

This is a library encapsulating the algorithm developed by me for time series forecasting in general. It has been used for Inventory Management (particularly Sales Forecasting), Liquidation Forecasting and numerous other projects of the Syngenta INPU data science intern team.

Parameters

The library has the following parameters. Some of them have default values but its better to tune them to optimal values for best results.

Usage

This library can be used in two different ways. But in both ways, you have to perform these steps first: