In this work, three machine learning techniques are used to determine dependency of white wine quality on eleven wine characteristic. Machine learning techniques are compared by calculating the level of accuracy of the model.
The wine quality dataset is used in this report. The wine dataset is a collection of white and red wines. The dataset is publicly available at https://archive.ics.uci.edu/ml/datasets/wine+quality. This report uses only the white wine data as it includes more observations.
This report is structured in three sections. The next section explains the methods and analysis used including data cleaning, data exploration and visualization, and the modelling approach. The results section presents the modelling results and discusses the model performance. The final section gives a brief summary of the report, its limitations and future work.
