Published on November 24, 2021
In Deep Tech

A Guide to VARMA with Grid Search in Time-Series Modelling

The main focus of the article is to implement a VARMA model using the Grid search approach. Where the work of grid search is to find the best-fit parameters for a time-series model.

By Yugesh Verma

Finding the best values of a machine learning model’s hyperparameters is important in order to build an efficient predictive model. In time-series modelling also, finding optimal values of the hyperparameters of a model is necessary for accurate forecasting. Grid search is a popular technique for such purposes. In this article, we will discuss how to use the grid search technique with a VARMA model in time series modelling for multivariate time series analysis. The major points that we will discuss here are listed below. Table of Contents What is Grid Search?What is VARMA?VARMA with Grid SearchImplementing VARMA with Grid Search What is Grid Search? In machine learning, most of the models like the random forest, decision trees, and support vector machines include para

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Yugesh Verma

Yugesh is a graduate in automobile engineering and worked as a data analyst intern. He completed several Data Science projects. He has a strong interest in Deep Learning and writing blogs on data science and machine learning.