DIAGNOSING THE QUALITY OF WINE USING A ADAPTING DECISION TREE CLASSIFIER FOR STREAMING DATA
Vo Ngoc Truong Duy , Vo Van Phuc , Tran Duy Khang , Ngo Ho Anh Khoi
Abstract: The research is focused on exploring the applications of Artificial Intelligence algorithms in handling diagnostic wine quality data. The article discusses the successful implementation of the Decision Tree algorithm for this purpose. This drives the main research goal, which revolves around integrating the Decision Tree with flexible sliding window techniques that can continuously adapt and update over time. The primary objective of the study is to address the wine quality diagnostic problem. Alongside this goal, there are additional smaller objectives to achieve. The initial step involves studying and researching theoretical foundations and measurement methods, as well as analyzing wine quality. Lastly, the goal of deploying a test application is set, aiming to create a Wine Quality Diagnostic Page. The interface of the page is designed to be user-friendly, intuitive, and informative about the functioning and content of the wine quality diagnostic method.
Keywords: Wine quality diagnosis, Decision Tree algorithm, AI application.
Wine Diagnosing
| Features | Description |
|---|---|
| Fixed acidity | Measure of non-volatile or non-volatile acids (g/L) |
| Volatile acidity | Measure of easily vaporizable acids in wine (g/L) |
| Citric acid | Weak organic acid, added to wine as a natural preservative (g/L) |
| Residual sugar | Amount of natural sugars left over after fermentation (g/L) |
| Chlorides | Presence of mineral acids contributing to saltiness (g/L) |
| Free sulfur dioxide | Amount of SO2 not bound to other molecules (mg/L) |
| Total sulfur dioxide | Measure of combined and free forms of SO2 (mg/L) |
| Density | Measure of mass per unit volume (g/cm³) |
| pH | Describes acidity or alkalinity of the wine (3-4) |
| Sulphates | Chemical additive contributing to SO2 production (g/L) |
| Alcohol | Percentage of alcohol content in the wine |
| Quality | Rating scale from 1 to 10 based on sensory data |
| Predicted Label | Decision value indicating red (1) or white (0) wine |
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