Wine Quality Analysis Using Artificial Intelligence and Machine Learning

Name: Wine Quality Analysis Using Artificial Intelligence and Machine Learning
Brand: LAP LAMBERT Academic Publishing
SKU: 9786206766896
Price: 866 CZK
Availability: InStock

Autor: Anita Mahajan, Neha Sharma

Jazyk:

Vazba: Brožovaná

Vydavatel: LAP LAMBERT Academic Publishing

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

866 Kč

The wine quality is important for the consumers as well as for the wine industry. The traditional (e...

Informace o knize

Autor

Anita Mahajan, Neha Sharma

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2023

Stránek

EAN

9786206766896

ISBN

6206766896

Enbook ID

44039755

Vydavatel

LAP LAMBERT Academic Publishing

Hmotnost

143

Rozměry

150 x 220 x 6

Kompletní popis

The wine quality is important for the consumers as well as for the wine industry. The traditional (expert wine tester) way of measuring wine quality might be expensive and time-consuming. Nowadays, machine learning models are foremost tools to replace human intervention. As a sub field of Artificial Intelligence (AI), Machine Learning (ML) aims to understand the structure of the data and fit it into models, which later can be used on unseen data to achieve the desired task. Machine Learning has been widely used in various sectors such as Businesses, Medical, and Astrophysics to name a few and many other scientific problems. Inspired by success of Artificial Intelligence in various different sectors here, we can use it for wine quality prediction based on various physicochemical properties of wine. Among various machine learning methods, we analyze the performance of Extremely randomized trees (Extra trees), Extreme Gradient Boosting (XG Boost) and Light gradient-boosting machine (Light GBM) ensemble ML methods. This work demonstrates how statistical data analysis can be used to identify the components that mainly control the wine quality prior to the production.

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Wine Quality Analysis Using Artificial Intelligence and Machine Learning

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Kompletní popis

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