# 2022類神經網路HW2 — Data

来源：https://www.kaggle.com/competitions/2022-neural-network/data

采集时间：2026-10-20T08:42:29Z

Analysis the data, and predict the quality of the wine.

Input variables (based on physicochemical tests):
1 - fixed acidity
2 - volatile acidity
3 - citric acid
4 - residual sugar
5 - chlorides
6 - free sulfur dioxide
7 - total sulfur dioxide
8 - density
9 - pH
10 - sulphates
11 - alcohol
Output variable (based on sensory data):
12 - quality (score between 0 and 10)

To simply the problem, we transfer quality to two class: bad and good.
If quality <= 5: bad (0)
If quality > 5: good (1)

Acknowledgements: [https://archive.ics.uci.edu/ml/datasets/wine+quality](https://archive.ics.uci.edu/ml/datasets/wine+quality)