This dataset contains data for variants of the Portuguese

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Task #1 - Classification for Wine The Wine Dataset

The dataset files are provided for you:

• wine_train.arff (labeled training set, 1599 instances)

 

This dataset is adapted from:

P. Cortez, A. Cerdeira, F. Almeida, T. Matos and J. Reis. Modelling wine preferences by data mining from physicochemical properties. In Decision Support Systems, Elsevier, 47(4):547-553. ISSN: 0167- 9236.

 

This dataset contains data for variants of the Portuguese "Vinho Verde" wine. For each variant, 11 chemical features were measured. Each of these is a numeric attribute. They are:

• fixed acidity

• volatile acidity

• citric acid

• residual sugar

• chlorides numeric

• free sulfur dioxide

• total sulfur dioxide

• density

• pH

• sulphates

• alcohol

 

Each variant was tasted by three experts. Their ratings have been combined into a single quality label: "good" or "bad" Therefore this is a binary classification problem with numeric attributes.

 

Task 1 - Part 1: Examine/Explore the Data [Total 15 Marks ]

It is a good idea to inspect your data by hand before running any machine learning experiments, to ensure that the dataset is in the correct format and that you understand what the dataset contains.

 

Firstly, view wine_train.arff. You should see something like this:

 

The files are in ARFF (Attribute-Relation File Format), a text format developed for Weka. At the top of each file you will see a list of attributes, followed by a data section with rows of comma separated values, one for each instance.

 

For this assignment you will not need to deal with the ARFF format directly, as Weka will handle reading and writing ARFF files for you. In future experiments you may have to convert between ARFF and another data format. (You can close the text editor.)

Attachments:

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